Internet DRAFT - draft-irtf-t2trg-iot-seccons
draft-irtf-t2trg-iot-seccons
Network Working Group O. Garcia-Morchon
Internet-Draft Philips IP&S
Intended status: Informational S. Kumar
Expires: June 16, 2019 Philips Research
M. Sethi
Ericsson
December 13, 2018
State-of-the-Art and Challenges for the Internet of Things Security
draft-irtf-t2trg-iot-seccons-16
Abstract
The Internet of Things (IoT) concept refers to the usage of standard
Internet protocols to allow for human-to-thing and thing-to-thing
communication. The security needs for IoT systems are well-
recognized and many standardization steps to provide security have
been taken, for example, the specification of Constrained Application
Protocol (CoAP) secured with Datagram Transport Layer Security
(DTLS). However, security challenges still exist, not only because
there are some use cases that lack a suitable solution, but also
because many IoT devices and systems have been designed and deployed
with very limited security capabilities. In this document, we first
discuss the various stages in the lifecycle of a thing. Next, we
document the security threats to a thing and the challenges that one
might face to protect against these threats. Lastly, we discuss the
next steps needed to facilitate the deployment of secure IoT systems.
This document can be used by implementors and authors of IoT
specifications as a reference for details about security
considerations while documenting their specific security challenges,
threat models, and mitigations.
This document is a product of the IRTF Thing-to-Thing Research Group
(T2TRG).
Status of This Memo
This Internet-Draft is submitted in full conformance with the
provisions of BCP 78 and BCP 79.
Internet-Drafts are working documents of the Internet Engineering
Task Force (IETF). Note that other groups may also distribute
working documents as Internet-Drafts. The list of current Internet-
Drafts is at https://datatracker.ietf.org/drafts/current/.
Internet-Drafts are draft documents valid for a maximum of six months
and may be updated, replaced, or obsoleted by other documents at any
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time. It is inappropriate to use Internet-Drafts as reference
material or to cite them other than as "work in progress."
This Internet-Draft will expire on June 16, 2019.
Copyright Notice
Copyright (c) 2018 IETF Trust and the persons identified as the
document authors. All rights reserved.
This document is subject to BCP 78 and the IETF Trust's Legal
Provisions Relating to IETF Documents
(https://trustee.ietf.org/license-info) in effect on the date of
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Table of Contents
1. Introduction . . . . . . . . . . . . . . . . . . . . . . . . 3
2. The Thing Lifecycle . . . . . . . . . . . . . . . . . . . . . 4
3. Security Threats and Managing Risk . . . . . . . . . . . . . 7
4. State-of-the-Art . . . . . . . . . . . . . . . . . . . . . . 11
4.1. IP-based IoT Protocols and Standards . . . . . . . . . . 11
4.2. Existing IP-based Security Protocols and Solutions . . . 14
4.3. IoT Security Guidelines . . . . . . . . . . . . . . . . . 16
5. Challenges for a Secure IoT . . . . . . . . . . . . . . . . . 19
5.1. Constraints and Heterogeneous Communication . . . . . . . 19
5.1.1. Resource Constraints . . . . . . . . . . . . . . . . 19
5.1.2. Denial-of-Service Resistance . . . . . . . . . . . . 20
5.1.3. End-to-end security, protocol translation, and the
role of middleboxes . . . . . . . . . . . . . . . . . 21
5.1.4. New network architectures and paradigm . . . . . . . 23
5.2. Bootstrapping of a Security Domain . . . . . . . . . . . 23
5.3. Operational Challenges . . . . . . . . . . . . . . . . . 24
5.3.1. Group Membership and Security . . . . . . . . . . . . 24
5.3.2. Mobility and IP Network Dynamics . . . . . . . . . . 25
5.4. Secure software update and cryptographic agility . . . . 26
5.5. End-of-Life . . . . . . . . . . . . . . . . . . . . . . . 28
5.6. Verifying device behavior . . . . . . . . . . . . . . . . 28
5.7. Testing: bug hunting and vulnerabilities . . . . . . . . 29
5.8. Quantum-resistance . . . . . . . . . . . . . . . . . . . 30
5.9. Privacy protection . . . . . . . . . . . . . . . . . . . 31
5.10. Reverse engineering considerations . . . . . . . . . . . 32
5.11. Trustworthy IoT Operation . . . . . . . . . . . . . . . . 33
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6. Conclusions and Next Steps . . . . . . . . . . . . . . . . . 34
7. Security Considerations . . . . . . . . . . . . . . . . . . . 34
8. IANA Considerations . . . . . . . . . . . . . . . . . . . . . 34
9. Acknowledgments . . . . . . . . . . . . . . . . . . . . . . . 35
10. Informative References . . . . . . . . . . . . . . . . . . . 35
Authors' Addresses . . . . . . . . . . . . . . . . . . . . . . . 47
1. Introduction
The Internet of Things (IoT) denotes the interconnection of highly
heterogeneous networked entities and networks that follow a number of
different communication patterns such as: human-to-human (H2H),
human-to-thing (H2T), thing-to-thing (T2T), or thing-to-things
(T2Ts). The term IoT was first coined by the Auto-ID center
[AUTO-ID] in 1999 which had envisioned a world where every physical
object is tagged with a radio-frequency identification (RFID) tag
having a globally unique identifier. This would not only allow
tracking of objects in real-time but also allow querying of data
about them over the Internet. However, since then, the meaning of
the Internet of Things has expanded and now encompasses a wide
variety of technologies, objects and protocols. It is not surprising
that the IoT has received significant attention from the research
community to (re)design, apply, and use standard Internet technology
and protocols for the IoT.
The things that are part of the Internet of Things are computing
devices that understand and react to the environment they reside in.
These things are also often referred to as smart objects or smart
devices. The introduction of IPv6 [RFC6568] and CoAP [RFC7252] as
fundamental building blocks for IoT applications allows connecting
IoT hosts to the Internet. This brings several advantages including:
(i) a homogeneous protocol ecosystem that allows simple integration
with other Internet hosts; (ii) simplified development for devices
that significantly vary in their capabilities; (iii) a unified
interface for applications, removing the need for application-level
proxies. These building blocks greatly simplify the deployment of
the envisioned scenarios which range from building automation to
production environments and personal area networks.
This document presents an overview of important security aspects for
the Internet of Things. We begin by discussing the lifecycle of a
thing in Section 2. In Section 3, we discuss security threats for
the IoT and methodologies for managing these threats when designing a
secure system. Section 4 reviews existing IP-based (security)
protocols for the IoT and briefly summarizes existing guidelines and
regulations. Section 5 identifies remaining challenges for a secure
IoT and discusses potential solutions. Section 6 includes final
remarks and conclusions. This document can be used by IoT standards
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specifications as a reference for details about security
considerations applying to the specified system or protocol.
The first draft version of this document was submitted in March 2011.
Initial draft versions of this document were presented and discussed
during the CORE meetings at IETF 80 and later. Discussions on
security lifecycle at IETF 92 (March 2015) evolved into more general
security considerations. Thus, the draft was selected to address the
T2TRG work item on the security considerations and challenges for the
Internet of Things. Further updates of the draft were presented and
discussed during the T2TRG meetings at IETF 96 (July 2016) and IETF
97 (November 2016) and at the joint interim in Amsterdam (March
2017). This document has been reviewed by, commented on, and
discussed extensively for a period of nearly six years by a vast
majority of T2TRG and related group members; the number of which
certainly exceeds 100 individuals. It is the consensus of T2TRG that
the security considerations described in this document should be
published in the IRTF Stream of the RFC series. This document does
not constitute a standard.
2. The Thing Lifecycle
The lifecycle of a thing refers to the operational phases of a thing
in the context of a given application or use case. Figure 1 shows
the generic phases of the lifecycle of a thing. This generic
lifecycle is applicable to very different IoT applications and
scenarios. For instance, [RFC7744] provides an overview of relevant
IoT use cases.
In this document, we consider a Building Automation and Control (BAC)
system to illustrate the lifecycle and the meaning of these different
phases. A BAC system consists of a network of interconnected nodes
that performs various functions in the domains of HVAC (Heating,
Ventilating, and Air Conditioning), lighting, safety, etc. The nodes
vary in functionality and a large majority of them represent
resource-constrained devices such as sensors and luminaries. Some
devices may be battery operated or may rely on energy harvesting.
This requires us to also consider devices that sleep during their
operation to save energy. In our BAC scenario, the life of a thing
starts when it is manufactured. Due to the different application
areas (i.e., HVAC, lighting, or safety) nodes/things are tailored to
a specific task. It is therefore unlikely that one single
manufacturer will create all nodes in a building. Hence,
interoperability as well as trust bootstrapping between nodes of
different vendors is important.
The thing is later installed and commissioned within a network by an
installer during the bootstrapping phase. Specifically, the device
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identity and the secret keys used during normal operation may be
provided to the device during this phase. Different subcontractors
may install different IoT devices for different purposes.
Furthermore, the installation and bootstrapping procedures may not be
a discrete event and may stretch over an extended period. After
being bootstrapped, the device and the system of things are in
operational mode and execute the functions of the BAC system. During
this operational phase, the device is under the control of the system
owner and used by multiple system users. For devices with lifetimes
spanning several years, occasional maintenance cycles may be
required. During each maintenance phase, the software on the device
can be upgraded or applications running on the device can be
reconfigured. The maintenance tasks can be performed either locally
or from a backend system. Depending on the operational changes to
the device, it may be required to re-bootstrap at the end of a
maintenance cycle. The device continues to loop through the
operational phase and the eventual maintenance phases until the
device is decommissioned at the end of its lifecycle. However, the
end-of-life of a device does not necessarily mean that it is
defective and rather denotes a need to replace and upgrade the
network to the next-generation devices for additional functionality.
Therefore, the device can be removed and re-commissioned to be used
in a different system under a different owner thereby starting the
lifecycle all over again.
We note that the presented lifecycle represents to some extent a
simplified model. For instance, it is possible to argue that the
lifecycle does not start when a tangible device is manufactured but
rather when the oldest bit of code that ends up in the device - maybe
from an open source project or from the used operating system - was
written. Similarly, the lifecycle could also include an on-the-shelf
phase where the device is in the supply-chain before an owner/user
purchases and installs it. Another phase could involve the device
being re-badged by some vendor who is not the original manufacturer.
Such phases can significantly complicate other phases such as
maintenance and bootstrapping. Finally, other potential end-states
can be, e.g., a vendor that no longer supports a device type because
it is at end-of-life or a situation in which a device is simply
forgotten but remains functional.
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_Manufactured _SW update _Decommissioned
/ / /
| _Installed | _ Application | _Removed &
| / | / reconfigured | / replaced
| | _Commissioned | | | |
| | / | | | | _Reownership &
| | | _Application | | _Application | | / recommissioned
| | | / running | | / running | | |
| | | | | | | | | | \\
+##+##+###+#############+##+##+#############+##+##+##############>>>
\/ \______________/ \/ \_____________/ \___/ time //
/ / \ \ \
Bootstrapping / Maintenance & \ Maintenance &
/ re-bootstrapping \ re-bootstrapping
Operational Operational
Figure 1: The lifecycle of a thing in the Internet of Things
Security is a key requirement in any communication system. However,
security is an even more critical requirement in real-world IoT
deployments for several reasons. First, compromised IoT systems can
not only endanger the privacy and security of a user, but can also
cause physical harm. This is because IoT systems often comprise
sensors, actuators and other connected devices in the physical
environment of the user which could adversely affect the user if they
are compromised. Second, a vulnerable IoT system means that an
attacker can alter the functionality of a device from a given
manufacturer. This not only affects the manufacturer's brand image,
but can also leak information that is very valuable for the
manufacturer (such as proprietary algorithms). Third, the impact of
attacking an IoT system goes beyond a specific device or an isolated
system since compromised IoT systems can be misused at scale. For
example, they may be used to perform a Distributed Denial of Service
(DDoS) attack that limits the availability of other networks and
services. The fact that many IoT systems rely on standard IP
protocols allows for easier system integration, but this also makes
attacks on standard IP protocols widely applicable in other
environments. This results in new requirements regarding the
implementation of security.
The term security subsumes a wide range of primitives, protocols, and
procedures. For instance, the term security includes services such
as confidentiality, authentication, integrity, authorization, source
authentication, and availability. The term security often also
includes augmented services such as duplicate detection and detection
of stale packets (timeliness). These security services can be
implemented through a combination of cryptographic mechanisms such as
block ciphers, hash functions, and signature algorithms; as well as
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non-cryptographic mechanisms that implement authorization and other
security policy enforcement aspects. For ensuring security in IoT
networks, one should not only focus on the required security
services, but also pay special attention to how the services are
realized in the overall system.
3. Security Threats and Managing Risk
Security threats in related IP protocols have been analyzed in
multiple documents including Hypertext Transfer Protocol (HTTP) over
Transport Layer Security (TLS) (HTTPS) [RFC2818], Constrained
Application Protocol (COAP) [RFC7252], IPv6 over Low-Power Wireless
Personal Area Networks (6LoWPAN) [RFC4919], Access Node Control
Protocol (ANCP) [RFC5713], Domain Name System (DNS) [RFC3833], IPv6
Neighbor Discovery (ND) [RFC3756], and Protocol for Carrying
Authentication and Network Access (PANA) [RFC4016]. In this section,
we specifically discuss the threats that could compromise an
individual thing or the network as a whole. Some of these threats
might go beyond the scope of Internet protocols but we gather them
here for the sake of completeness. The threats in the following list
are not in any particular order and some threats might be more
critical than others depending on the deployment scenario under
consideration:
1. Vulnerable Software/Code: Things in the Internet of Things rely
on software that might contain severe bugs and/or bad design
choices. This makes the things vulnerable to many different
types of attacks, depending on the criticality of the bugs,
e.g., buffer overflows or lack of authentication. This can be
considered as one of the most important security threat. The
large-scale distributed denial-of-service (DDoS) attack,
popularly known as the Mirai botnet [mirai], was caused by
things that had well-known or easy-to-guess passwords for
configuration.
2. Privacy threat: The tracking of a thing's location and usage may
pose a privacy risk to people around it. For instance, an
attacker can infer privacy sensitive information from the data
gathered and communicated by individual things. Such
information may subsequently be sold to interested parties for
marketing purposes and targeted advertising. In extreme cases,
such information might be used to track dissidents in oppressive
regimes. Unlawful surveillance and interception of traffic to/
from a thing by intelligence agencies is also a privacy threat.
3. Cloning of things: During the manufacturing process of a thing,
an untrusted factory can easily clone the physical
characteristics, firmware/software, or security configuration of
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the thing. Deployed things might also be compromised and their
software reverse engineered allowing for cloning or software
modifications. Such a cloned thing may be sold at a cheaper
price in the market, and yet can function normally as a genuine
thing. For example, two cloned devices can still be associated
and work with each other. In the worst-case scenario, a cloned
device can be used to control a genuine device or perform an
attack. One should note here, that an untrusted factory may
also change functionality of the cloned thing, resulting in
degraded functionality with respect to the genuine thing
(thereby, inflicting potential damage to the reputation of the
original thing manufacturer). Moreover, additional
functionality can be introduced in the cloned thing. An example
of such functionality is a backdoor.
4. Malicious substitution of things: During the installation of a
thing, a genuine thing may be substituted with a similar variant
(of lower quality) without being detected. The main motivation
may be cost savings, where the installation of lower-quality
things (for example, non-certified products) may significantly
reduce the installation and operational costs. The installers
can subsequently resell the genuine things to gain further
financial benefits. Another motivation may be to inflict damage
to the reputation of a competitor's offerings.
5. Eavesdropping attack: During the commissioning of a thing into a
network, it may be susceptible to eavesdropping, especially if
operational keying materials, security parameters, or
configuration settings, are exchanged in clear using a wireless
medium or if used cryptographic algorithms are not suitable for
the envisioned lifetime of the device and the system. After
obtaining the keying material, the attacker might be able to
recover the secret keys established between the communicating
entities, thereby compromising the authenticity and
confidentiality of the communication channel, as well as the
authenticity of commands and other traffic exchanged over this
communication channel. When the network is in operation, T2T
communication can be eavesdropped if the communication channel
is not sufficiently protected or if a session key is compromised
due to protocol weaknesses. An adversary may also be able to
eavesdrop if keys are not renewed or updated appropriately.
Lastly, messages can also be recorded and decrypted offline at a
later point of time. The Venona project [venona-project] is one
such example where messages were recorded for offline
decryption.
6. Man-in-the-middle attack: Both the commissioning phase and
operational phases may also be vulnerable to man-in-the-middle
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attacks. For example, when keying material between
communicating entities is exchanged in the clear and the
security of the key establishment protocol depends on the tacit
assumption that no third party can eavesdrop during the
execution of this protocol. Additionally, device authentication
or device authorization may be non-trivial, or may need support
of a human decision process, since things usually do not have
a-priori knowledge about each other and cannot always
differentiate friends and foes via completely automated
mechanisms.
7. Firmware attacks: When a thing is in operation or maintenance
phase, its firmware or software may be updated to allow for new
functionality or new features. An attacker may be able to
exploit such a firmware upgrade by maliciously replacing the
thing's firware, thereby influencing its operational behavior.
For example, an attacker could add a piece of malicious code to
the firmware that will cause it to periodically report the
energy usage of the thing to a data repository for analysis.
The attacker can then use this information to determine when a
home or enterprise (where the thing is installed) is unoccupied
and break in. Similarly, devices whose software has not been
properly maintained and updated might contain vulnerabilities
that might be exploited by attackers to replace the firmware on
the device.
8. Extraction of private information: IoT devices (such as sensors,
actuators, etc.) are often physically unprotected in their
ambient environment and they could easily be captured by an
attacker. An attacker with physical access may then attempt to
extract private information such as keys (for example, device's
key, private-key, group key), sensed data (for example,
healthcare status of a user), configuration parameters (for
example, the Wi-Fi key), or proprietary algorithms (for example,
algorithm performing some data analytics task). Even when the
data originating from a thing is encrypted, attackers can
perform traffic analysis to deduce meaningful information which
might compromise the privacy of the thing's owner and/or user.
9. Routing attack: As highlighted in [ID-Daniel], routing
information in IoT networks can be spoofed, altered, or
replayed, in order to create routing loops, attract/repel
network traffic, extend/shorten source routes, etc. A non-
exhaustive list of routing attacks includes 1) Sinkhole attack
(or blackhole attack), where an attacker declares himself to
have a high-quality route/path to the base station, thus
allowing him to do manipulate all packets passing through it. 2)
Selective forwarding, where an attacker may selectively forward
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packets or simply drop a packet. 3) Wormhole attack, where an
attacker may record packets at one location in the network and
tunnel them to another location, thereby influencing perceived
network behavior and potentially distorting statistics, thus
greatly impacting the functionality of routing. 4) Sybil attack,
whereby an attacker presents multiple identities to other things
in the network. We refer to [ID-Daniel] for further router
attacks and a more detailed description.
10. Elevation of privilege: An attacker with low privileges can
misuse additional flaws in the implemented authentication and
authorization mechanisms of a thing to gain more privileged
access to the thing and its data.
11. Denial-of-Service (DoS) attack: Often things have very limited
memory and computation capabilities. Therefore, they are
vulnerable to resource exhaustion attack. Attackers can
continuously send requests to specific things so as to deplete
their resources. This is especially dangerous in the Internet
of Things since an attacker might be located in the backend and
target resource-constrained devices that are part of a
constrained node network [RFC7228]. DoS attack can also be
launched by physically jamming the communication channel.
Network availability can also be disrupted by flooding the
network with a large number of packets. On the other hand,
things compromised by attackers can be used to disrupt the
operation of other networks or systems by means of a Distributed
DoS (DDoS) attack.
To deal with above threats it is required to find and apply suitable
security mitigations. However, new threats and exploits appear on a
daily basis and products are deployed in different environments prone
to different types of threats. Thus, ensuring a proper level of
security in an IoT system at any point of time is challenging. To
address this challenge, some of the following methodologies can be
used:
1. A Business Impact Analysis (BIA) assesses the consequences of the
loss of basic security attributes: confidentiality, integrity and
availability in an IoT system. These consequences might include
the impact from lost data, reduced sales, increased expenses,
regulatory fines, customer dissatisfaction, etc. Performing a
business impact analysis allows a business to determine the
relevance of having a proper security design.
2. A Risk Assessment (RA) analyzes security threats to an IoT system
while considering their likelihood and impact. It also includes
categorizing each of them with a risk level. Risks classified as
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moderate or high must be mitigated, i.e., the security
architecture should be able to deal with those threat.
3. A privacy impact assessment (PIA) aims at assessing the
Personally Identifiable Information (PII) that is collected,
processed, or used in an IoT system. By doing so, the goal is to
fulfill applicable legal requirements, determine risks and
effects of manipulation and loss of PII.
4. Procedures for incident reporting and mitigation refer to the
methodologies that allow becoming aware of any security issues
that affect an IoT system. Furthermore, this includes steps
towards the actual deployment of patches that mitigate the
identified vulnerabilities.
BIA, RA, and PIA should generally be realized during the creation of
a new IoT system or when deploying significant system/feature
upgrades. In general, it is recommended to re-assess them on a
regular basis taking into account new use cases and/or threats. The
way a BIA, RA, PIA are performed depends on the environment and the
industry. More information can be found in NIST documents such as
[NISTSP800-34r1], [NISTSP800-30r1], and [NISTSP800-122].
4. State-of-the-Art
This section is organized as follows. Section 4.1 summarizes state-
of-the-art on IP-based IoT systems, within IETF and in other
standardization bodies. Section 4.2 summarizes state-of-the-art on
IP-based security protocols and their usage. Section 4.3 discusses
guidelines and regulations for securing IoT as proposed by other
bodies. Note that the references included in this section are a
representative of the state-of-the-art at the point of writing and
they are by no means exhaustive. The references are also at varying
levels of maturity, and thus, it is advisable to review their
specific status.
4.1. IP-based IoT Protocols and Standards
Nowadays, there exists a multitude of control protocols for IoT. For
BAC systems, the ZigBee standard [ZB], BACNet [BACNET], and DALI
[DALI] play key roles. Recent trends, however, focus on an all-IP
approach for system control.
In this setting, a number of IETF working groups are designing new
protocols for resource-constrained networks of smart things. The
6LoWPAN working group [WG-6LoWPAN] for example has defined methods
and protocols for the efficient transmission and adaptation of IPv6
packets over IEEE 802.15.4 networks [RFC4944].
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The CoRE working group [WG-CoRE] has specified the Constrained
Application Protocol (CoAP) [RFC7252]. CoAP is a RESTful protocol
for constrained devices that is modeled after HTTP and typically runs
over UDP to enable efficient application-level communication for
things.
In many smart object networks, the smart objects are dispersed and
have intermittent reachability either because of network outages or
because they sleep during their operational phase to save energy. In
such scenarios, direct discovery of resources hosted on the
constrained server might not be possible. To overcome this barrier,
the CoRE working group is specifying the concept of a Resource
Directory (RD) [ID-rd]. The Resource Directory hosts descriptions of
resources which are located on other nodes. These resource
descriptions are specified as CoRE link format [RFC6690].
While CoAP defines a standard communication protocol, a format for
representing sensor measurements and parameters over CoAP is
required. The Sensor Measurement Lists (SenML) [RFC8428] is a
specification that defines media types for simple sensor measurements
and parameters. It has a minimalistic design so that constrained
devices with limited computational capabilities can easily encode
their measurements and, at the same time, servers can efficiently
collect large number of measurements.
In many IoT deployments, the resource-constrained smart objects are
connected to the Internet via a gateway that is directly reachable.
For example, an IEEE 802.11 Access Point (AP) typically connects the
client devices to the Internet over just one wireless hop. However,
some deployments of smart object networks require routing between the
smart objects themselves. The IETF has therefore defined the IPv6
Routing Protocol for Low-Power and Lossy Networks (RPL) [RFC6550].
RPL provides support for multipoint-to-point traffic from resource-
constrained smart objects towards a more resourceful central control
point, as well as point-to-multipoint traffic in the reverse
direction. It also supports point-to-point traffic between the
resource-constrained devices. A set of routing metrics and
constraints for path calculation in RPL are also specified [RFC6551].
The IPv6 over Networks of Resource-constrained Nodes (6lo) [WG-6lo]
working group of the IETF has specified how IPv6 packets can be
transmitted over various link layer protocols that are commonly
employed for resource-constrained smart object networks. There is
also ongoing work to specify IPv6 connectivity for a Non-Broadcast
Multi-Access (NBMA) mesh network that is formed by IEEE 802.15.4
TimeSlotted Channel Hopping (TSCH} links [ID-6tisch]. Other link
layer protocols for which IETF has specified or is currently
specifying IPv6 support include Bluetooth [RFC7668], Digital Enhanced
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Cordless Telecommunications (DECT) Ultra Low Energy (ULE) air
interface [RFC8105], and Near Field Communication (NFC) [ID-6lonfc].
Baker and Meyer [RFC6272] identify which IP protocols can be used in
smart grid environments. They give advice to smart grid network
designers on how they can decide on a profile of the Internet
protocol suite for smart grid networks.
The Low Power Wide-Area Network (LPWAN) working [WG-LPWAN] group is
analyzing features, requirements, and solutions to adapt IP-based
protocols to networks such as LORA [lora], SigFox [sigfox], NB-IoT
[nbiot], etc. These networking technologies enable a smart thing to
run for years on a single coin-cell by relying on a star network
topology and using optimized radio modulation with frame sizes in the
order of tens of bytes. Such networks bring new security challenges
since most existing security mechanism do not work well with such
resource constraints.
JavaScript Object Notation (JSON) is a lightweight text
representation format for structured data [RFC8259]. It is often
used for transmitting serialized structured data over the network.
IETF has defined specifications for encoding cryptographic keys,
encrypted content, signed content, and claims to be transferred
between two parties as JSON objects. They are referred to as JSON
Web Keys (JWK) [RFC7517], JSON Web Encryption (JWE) [RFC7516], JSON
Web Signatures (JWS) [RFC7515] and JSON Web Token (JWT) [RFC7519].
An alternative to JSON, Concise Binary Object Representation (CBOR)
[RFC7049] is a concise binary data format that is used for
serialization of structured data. It is designed for resource-
constrained nodes and therefore it aims to provide a fairly small
message size with minimal implementation code, and extensibility
without the need for version negotiation. CBOR Object Signing and
Encryption (COSE) [RFC8152] specifies how to encode cryptographic
keys, message authentication codes, encrypted content, and signatures
with CBOR.
The Light-Weight Implementation Guidance (LWIG) working group
[WG-LWIG] is collecting experiences from implementers of IP stacks in
constrained devices. The working group has already produced
documents such as RFC7815 [RFC7815] which defines how a minimal
Internet Key Exchange Version 2 (IKEv2) initiator can be implemented.
The Thing-2-Thing Research Group (T2TRG) [RG-T2TRG] is investigating
the remaining research issues that need to be addressed to quickly
turn the vision of IoT into a reality where resource-constrained
nodes can communicate with each other and with other more capable
nodes on the Internet.
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Additionally, industry alliances and other standardization bodies are
creating constrained IP protocol stacks based on the IETF work. Some
important examples of this include:
1. Thread [Thread]: Specifies the Thread protocol that is intended
for a variety of IoT devices. It is an IPv6-based network
protocol that runs over IEEE 802.15.4.
2. Industrial Internet Consortium [IIoT]: The consortium defines
reference architectures and security frameworks for development,
adoption and widespread use of Industrial Internet technologies
based on existing IETF standards.
3. Internet Protocol for Smart Objects IPSO [IPSO]: The alliance
specifies a common object model that enables application software
on any device to interoperate with other conforming devices.
4. OneM2M [OneM2M]: The standards body defines technical and API
specifications for IoT devices. It aims to create a service
layer that can run on any IoT device hardware and software.
5. Open Connectivity Foundation (OCF) [OCF]: The foundation develops
standards and certifications primarily for IoT devices that use
Constrained Application Protocol (CoAP) as the application layer
protocol.
6. Fairhair Alliance [Fairhair]: Specifies an IoT middleware to
enable a common IP network infrastructure between different
application standards used in building automation and lighting
systems such as BACnet, KNX and ZigBee.
7. OMA LWM2M [LWM2M]: OMA Lightweight M2M is a standard from the
Open Mobile Alliance for M2M and IoT device management. LWM2M
relies on CoAP as the application layer protocol and uses a
RESTful architecture for remote management of IoT devices.
4.2. Existing IP-based Security Protocols and Solutions
There are three main security objectives for IoT networks: 1.
protecting the IoT network from attackers. 2. protecting IoT
applications and thus, the things and users. 3. protecting the rest
of the Internet and other things from attacks that use compromised
things as an attack platform.
In the context of the IP-based IoT deployments, consideration of
existing Internet security protocols is important. There are a wide
range of specialized as well as general-purpose security solutions
for the Internet domain such as IKEv2/IPsec [RFC7296], Transport
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Layer Security (TLS) [RFC8446], Datagram Transport Layer Security
(DTLS) [RFC6347], Host Identity Protocol (HIP) [RFC7401], PANA
[RFC5191], Kerberos ([RFC4120]), Simple Authentication and Security
Layer (SASL) [RFC4422], and Extensible Authentication Protocol (EAP)
[RFC3748].
TLS provides security for TCP and requires a reliable transport.
DTLS secures and uses datagram-oriented protocols such as UDP. Both
protocols are intentionally kept similar and share the same ideology
and cipher suites. The CoAP base specification [RFC7252] provides a
description of how DTLS can be used for securing CoAP. It proposes
three different modes for using DTLS: the PreSharedKey mode, where
nodes have pre-provisioned keys for initiating a DTLS session with
another node, RawPublicKey mode, where nodes have asymmetric-key
pairs but no certificates to verify the ownership, and Certificate
mode, where public keys are certified by a certification authority.
An IoT implementation profile [RFC7925] is defined for TLS version
1.2 and DTLS version 1.2 that offers communication security for
resource-constrained nodes.
There is ongoing work to define an authorization and access-control
framework for resource-constrained nodes. The Authentication and
Authorization for Constrained Environments (ACE) [WG-ACE] working
group is defining a solution to allow only authorized access to
resources that are hosted on a smart object server and are identified
by a URI. The current proposal [ID-aceoauth] is based on the OAuth
2.0 framework [RFC6749] and it comes with profiles intended for
different communication scenarios, e.g. DTLS Profile for
Authentication and Authorization for Constrained Environments
[ID-acedtls].
OSCORE [ID-OSCORE] is a proposal that protects CoAP messages by
wrapping them in the CBOR Object Signing and Encryption (COSE)
[RFC8152] format. Thus, OSCORE falls in the category of object
security and it can be applied wherever CoAP can be used. The
advantage of OSCORE over DTLS is that it provides some more
flexibility when dealing with end-to-end security. Section 5.1.3
discusses this further.
The Automated Certificate Management Environment (ACME) [WG-ACME]
working group is specifying conventions for automated X.509
certificate management. This includes automatic validation of
certificate issuance, certificate renewal, and certificate
revocation. While the initial focus of working group is on domain
name certificates (as used by web servers), other uses in some IoT
deployments is possible.
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The Internet Key Exchange (IKEv2)/IPsec - as well as the less used
Host Identity protocol (HIP) - reside at or above the network layer
in the OSI model. Both protocols are able to perform an
authenticated key exchange and set up the IPsec for secure payload
delivery. Currently, there are also ongoing efforts to create a HIP
variant coined Diet HIP [ID-HIP-DEX] that takes constrained networks
and nodes into account at the authentication and key exchange level.
Migault et al. [ID-dietesp] are working on a compressed version of
IPsec so that it can easily be used by resource-constrained IoT
devices. They rely on the Internet Key Exchange Protocol version 2
(IKEv2) for negotiating the compression format.
The Extensible Authentication Protocol (EAP) [RFC3748] is an
authentication framework supporting multiple authentication methods.
EAP runs directly over the data link layer and, thus, does not
require the deployment of IP. It supports duplicate detection and
retransmission, but does not allow for packet fragmentation. The
Protocol for Carrying Authentication for Network Access (PANA) is a
network-layer transport for EAP that enables network access
authentication between clients and the network infrastructure. In
EAP terms, PANA is a UDP-based EAP lower layer that runs between the
EAP peer and the EAP authenticator.
4.3. IoT Security Guidelines
Attacks on and from IoT devices have become common in the last years,
for instance, large scale Denial of Service (DoS) attacks on the
Internet Infrastructure from compromised IoT devices. This fact has
prompted many different standards bodies and consortia to provide
guidelines for developers and the Internet community at large to
build secure IoT devices and services. A subset of the different
guidelines and ongoing projects are as follows:
1. Global System for Mobile Communications (GSM) Association (GSMA)
IoT security guidelines [GSMAsecurity]: GSMA has published a set
of security guidelines for the benefit of new IoT product and
service providers. The guidelines are aimed at device
manufacturers, service providers, developers and network
operators. An enterprise can complete an IoT Security Self-
Assessment to demonstrate that its products and services are
aligned with the security guidelines of the GSMA.
2. Broadband Internet Technical Advisory Group (BITAG) IoT Security
and Privacy Recommendations [BITAG]: BITAG has published
recommendations for ensuring security and privacy of IoT device
users. BITAG observes that many IoT devices are shipped from
the factory with software that is already outdated and
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vulnerable. The report also states that many devices with
vulnerabilities will not be fixed either because the
manufacturer does not provide updates or because the user does
not apply them. The recommendations include that IoT devices
should function without cloud and Internet connectivity, and
that all IoT devices should have methods for automatic secure
software updates.
3. United Kingdom Department for Digital, Culture, Media and Sport
(DCMS) [DCMS]: UK DCMS has released a report that includes a
list of 13 steps for improving IoT security. These steps, for
example, highlight the need for implementing a vulnerability
disclosure policy and keeping software updated. The report is
aimed at device manufacturers, IoT service providers, mobile
application developers and retailers.
4. Cloud Security Alliance (CSA) New Security Guidance for Early
Adopters of the IoT [CSA]: CSA recommendations for early
adopters of IoT encourages enterprises to implement security at
different layers of the protocol stack. It also recommends
implementation of an authentication/authorization framework for
IoT deployments. A complete list of recommendations is
available in the report [CSA].
5. United States Department of Homeland Security [DHS]: DHS has put
forth six strategic principles that would enable IoT developers,
manufacturers, service providers and consumers to maintain
security as they develop, manufacture, implement or use network-
connected IoT devices.
6. National Institute of Standards and Technology (NIST)
[NIST-Guide]: The NIST special publication urges enterprise and
US federal agencies to address security throughout the systems
engineering process. The publication builds upon the
International Organization for Standardization
(ISO)/International Electrotechnical Commission (IEC) 15288
standard and augments each process in the system lifecycle with
security enhancements.
7. National Institute of Standards and Technology (NIST)
[nist-lightweight-project]: NIST is running a project on
lightweight cryptography with the purpose of: (i) identifying
application areas for which standard cryptographic algorithms
are too heavy, classifying them according to some application
profiles to be determined; (ii) determining limitations in those
existing cryptographic standards; and (iii) standardizing
lightweight algorithms that can be used in specific application
profiles.
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8. Open Web Application Security Project (OWASP) [OWASP]: OWASP
provides security guidance for IoT manufactures, developers and
consumers. OWASP also includes guidelines for those who intend
to test and analyze IoT devices and applications.
9. IoT Security foundation [IoTSecFoundation]: IoT security
foundation has published a document that enlists various
considerations that need to be taken into account when
developing IoT applications. For example, the document states
that IoT devices could use hardware-root of trust to ensure that
only authorized software runs on the devices.
10. National Highway Traffic Safety Administration (NHTSA) [NHTSA]:
The US NHTSA provides guidance to the automotive industry for
improving the cyber security of vehicles. While some of the
guidelines are general, the document provides specific
recommendations for the automotive industry such as how various
automotive manufacturer can share cyber security vulnerabilities
discovered.
11. Best Current Practices (BCP) for IoT devices [ID-Moore]: This
document provides a list of minimum requirements that vendors of
Internet of Things (IoT) devices should to take into account
while developing applications, services and firmware updates in
order to reduce the frequency and severity of security incidents
that arise from compromised IoT devices.
12. European Union Agency for Network and Information Security
(ENISA) [ENISA-ICS]: ENISA published a document on communication
network dependencies for Industrial Control Systems
(ICS)/Supervisory Control And Data Acquisition (SCADA) systems
in which security vulnerabilities, guidelines and general
recommendations are summarized.
13. Internet Society Online Trust Alliance [ISOC-OTA]: The Internet
Society's IoT Trust Framework identifies the core requirements
manufacturers, service providers, distributors, purchasers and
policymakers need to understand, assess and embrace for
effective security and privacy as part of the Internet of
Things.
Other guideline and recommendation documents may exist or may later
be published. This list should be considered non-exhaustive.
Despite the acknowledgment that security in the Internet is needed
and the existence of multiple guidelines, the fact is that many IoT
devices and systems have very limited security. There are multiple
reasons for this. For instance, some manufactures focus on
delivering a product without paying enough attention to security.
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This may be because of lack of expertise or limited budget. However,
the deployment of such insecure devices poses a severe threat on the
privacy and safety of users. The vast amount of devices and their
inherent mobile nature also implies that an initially secure system
can become insecure if a compromised device gains access to the
system at some point in time. Even if all other devices in a given
environment are secure, this does not prevent external attacks caused
by insecure devices. Recently the Federal Communications Commission
(FCC) [FCC] has stated the need for additional regulation of IoT
systems. It is possible that we may see other such regional
regulations in the future.
5. Challenges for a Secure IoT
In this section, we take a closer look at the various security
challenges in the operational and technical features of IoT and then
discuss how existing Internet security protocols cope with these
technical and conceptual challenges through the lifecycle of a thing.
This discussion should neither be understood as a comprehensive
evaluation of all protocols, nor can it cover all possible aspects of
IoT security. Yet, it aims at showing concrete limitations and
challenges in some IoT design areas rather than giving an abstract
discussion. In this regard, the discussion handles issues that are
most important from the authors' perspectives.
5.1. Constraints and Heterogeneous Communication
Coupling resource-constrained networks and the powerful Internet is a
challenge because the resulting heterogeneity of both networks
complicates protocol design and system operation. In the following
we briefly discuss the resource constraints of IoT devices and the
consequences for the use of Internet Protocols in the IoT domain.
5.1.1. Resource Constraints
IoT deployments are often characterized by lossy and low-bandwidth
communication channels. IoT devices are also often constrained in
terms of CPU, memory, and energy budget available [RFC7228]. These
characteristics directly impact the design of protocols for the IoT
domain. For instance, small packet size limits at the physical layer
(127 Bytes in IEEE 802.15.4) can lead to (i) hop-by-hop fragmentation
and reassembly or (ii) small IP-layer maximum transmission unit
(MTU). In the first case, excessive fragmentation of large packets
that are often required by security protocols may open new attack
vectors for state exhaustion attacks. The second case might lead to
more fragmentation at the IP layer which commonly downgrades the
overall system performance due to packet loss and the need for
retransmission.
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The size and number of messages should be minimized to reduce memory
requirements and optimize bandwidth usage. In this context, layered
approaches involving a number of protocols might lead to worse
performance in resource-constrained devices since they combine the
headers of the different protocols. In some settings, protocol
negotiation can increase the number of exchanged messages. To
improve performance during basic procedures such as, for example,
bootstrapping, it might be a good strategy to perform those
procedures at a lower layer.
Small CPUs and scarce memory limit the usage of resource-expensive
cryptographic primitives such as public-key cryptography as used in
most Internet security standards. This is especially true if the
basic cryptographic blocks need to be frequently used or the
underlying application demands low delay.
There are ongoing efforts to reduce the resource consumption of
security protocols by using more efficient underlying cryptographic
primitives such as Elliptic Curve Cryptography [RFC8446]. The
specification of elliptic curve X25519 [ecc25519], stream ciphers
such as ChaCha [ChaCha], Diet HIP [ID-HIP-DEX], and ECC goups for
IKEv2 [RFC5903] are all examples of efforts to make security
protocols more resource efficient. Additionally, most modern
security protocols have been revised in the last few years to enable
cryptographic agility, making cryptographic primitives
interchangeable. However, these improvements are only a first step
in reducing the computation and communication overhead of Internet
protocols. The question remains if other approaches can be applied
to leverage key agreement in these heavily resource-constrained
environments.
A further fundamental need refers to the limited energy budget
available to IoT nodes. Careful protocol (re)design and usage is
required to reduce not only the energy consumption during normal
operation, but also under DoS attacks. Since the energy consumption
of IoT devices differs from other device classes, judgments on the
energy consumption of a particular protocol cannot be made without
tailor-made IoT implementations.
5.1.2. Denial-of-Service Resistance
The tight memory and processing constraints of things naturally
alleviate resource exhaustion attacks. Especially in unattended T2T
communication, such attacks are difficult to notice before the
service becomes unavailable (for example, because of battery or
memory exhaustion). As a DoS countermeasure, DTLS, IKEv2, HIP, and
Diet HIP implement return routability checks based on a cookie
mechanism to delay the establishment of state at the responding host
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until the address of the initiating host is verified. The
effectiveness of these defenses strongly depend on the routing
topology of the network. Return routability checks are particularly
effective if hosts cannot receive packets addressed to other hosts
and if IP addresses present meaningful information as is the case in
today's Internet. However, they are less effective in broadcast
media or when attackers can influence the routing and addressing of
hosts (for example, if hosts contribute to the routing infrastructure
in ad-hoc networks and meshes).
In addition, HIP implements a puzzle mechanism that can force the
initiator of a connection (and potential attacker) to solve
cryptographic puzzles with variable difficulties. Puzzle-based
defense mechanisms are less dependent on the network topology but
perform poorly if CPU resources in the network are heterogeneous (for
example, if a powerful Internet host attacks a thing). Increasing
the puzzle difficulty under attack conditions can easily lead to
situations where a powerful attacker can still solve the puzzle while
weak IoT clients cannot and are excluded from communicating with the
victim. Still, puzzle-based approaches are a viable option for
sheltering IoT devices against unintended overload caused by
misconfiguration or malfunctioning things.
5.1.3. End-to-end security, protocol translation, and the role of
middleboxes
The term end-to-end security often has multiple interpretations.
Here, we consider end-to-end security in the context end-to-end IP
connectivity, from a sender to a receiver. Services such as
confidentiality and integrity protection on packet data, message
authentication codes or encryption are typically used to provide end-
to-end security. These protection methods render the protected parts
of the packets immutable as rewriting is either not possible because
a) the relevant information is encrypted and inaccessible to the
gateway or b) rewriting integrity-protected parts of the packet would
invalidate the end-to-end integrity protection.
Protocols for constrained IoT networks are not exactly identical to
their larger Internet counterparts for efficiency and performance
reasons. Hence, more or less subtle differences between protocols
for constrained IoT networks and Internet protocols will remain.
While these differences can be bridged with protocol translators at
middleboxes, they may become major obstacles if end-to-end security
measures between IoT devices and Internet hosts are needed.
If access to data or messages by the middleboxes is required or
acceptable, then a diverse set of approaches for handling such a
scenario are available. Note that some of these approaches affect
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the meaning of end-to-end security in terms of integrity and
confidentiality since the middleboxes will be able to either decrypt
or modify partially the exchanged messages:
1. Sharing credentials with middleboxes enables them to transform
(for example, decompress, convert, etc.) packets and re-apply the
security measures after transformation. This method abandons
end-to-end security and is only applicable to simple scenarios
with a rudimentary security model.
2. Reusing the Internet wire format for IoT makes conversion between
IoT and Internet protocols unnecessary. However, it can lead to
poor performance in some use cases because IoT specific
optimizations (for example, stateful or stateless compression)
are not possible.
3. Selectively protecting vital and immutable packet parts with a
message authentication code or with encryption requires a careful
balance between performance and security. Otherwise this
approach might either result in poor performance or poor security
depending on which parts are selected for protection, where they
are located in the original packet, and how they are processed.
[ID-OSCORE] proposes a solution in this direction by encrypting
and integrity protecting most of the message fields except those
parts that a middlebox needs to read or change.
4. Homomorphic encryption techniques can be used in the middlebox to
perform certain operations. However, this is limited to data
processing involving arithmetic operations. Furthermore,
performance of existing libraries, for example, SEAL [SEAL] is
still too limited and homomorphic encryption techniques are not
widely applicable yet.
5. Message authentication codes that sustain transformation can be
realized by considering the order of transformation and
protection (for example, by creating a signature before
compression so that the gateway can decompress the packet without
recalculating the signature). Such an approach enables IoT
specific optimizations but is more complex and may require
application-specific transformations before security is applied.
Moreover, the usage of encrypted or integrity-protected data
prevents middleboxes from transforming packets.
6. Mechanisms based on object security can bridge the protocol
worlds, but still require that the two worlds use the same object
security formats. Currently the object security format based on
CBOR Object Signing and Encryption (COSE) [RFC8152] is different
from JSON Object Signing and Encryption (JOSE) [RFC7520] or
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Cryptographic Message Syntax (CMS) [RFC5652]. Legacy devices
relying on traditional Internet protocols will need to update to
the newer protocols for constrained environments to enable real
end-to-end security. Furthermore, middleboxes do not have any
access to the data and this approach does not prevent an attacker
who is capable of modifying relevant message header fields that
are not protected.
To the best of our knowledge, none of the mentioned security
approaches that focus on the confidentiality and integrity of the
communication exchange between two IP end-points provide the perfect
solution in this problem space.
5.1.4. New network architectures and paradigm
There is a multitude of new link layer protocols that aim to address
the resource-constrained nature of IoT devices. For example, the
IEEE 802.11 ah [IEEE802ah] has been specified for extended range and
lower energy consumption to support Internet of Things (IoT) devices.
Similarly, Low-Power Wide-Area Network (LPWAN) protocols such as LoRa
[lora], Sigfox [sigfox], NarrowBand IoT (NB-IoT) [nbiot] are all
designed for resource-constrained devices that require long range and
low bit rates. [RFC8376] provides an informational overview of the
set of LPWAN technologies being considered by the IETF. It also
identifies the potential gaps that exist between the needs of those
technologies and the goal of running IP in such networks. While
these protocols allow IoT devices to conserve energy and operate
efficiently, they also add additional security challenges. For
example, the relatively small MTU can make security handshakes with
large X509 certificates a significant overhead. At the same time,
new communication paradigms also allow IoT devices to communicate
directly amongst themselves with or without support from the network.
This communication paradigm is also referred to as Device-to-Device
(D2D) or Machine-to-Machine (M2M) or Thing-to-Thing (T2T)
communication and it is motivated by a number of features such as
improved network performance, lower latency and lower energy
requirements.
5.2. Bootstrapping of a Security Domain
Creating a security domain from a set of previously unassociated IoT
devices is a key operation in the lifecycle of a thing in an IoT
network. This aspect is further elaborated and discussed in the
T2TRG draft on bootstrapping [ID-bootstrap].
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5.3. Operational Challenges
After the bootstrapping phase, the system enters the operational
phase. During the operational phase, things can use the state
information created during the bootstrapping phase in order to
exchange information securely. In this section, we discuss the
security challenges during the operational phase. Note that many of
the challenges discussed in Section 5.1 apply during the operational
phase.
5.3.1. Group Membership and Security
Group key negotiation is an important security service for IoT
communication patterns in which a thing sends some data to multiple
things or data flows from multiple things towards a thing. All
discussed protocols only cover unicast communication and therefore,
do not focus on group-key establishment. This applies in particular
to (D)TLS and IKEv2. Thus, a solution is required in this area. A
potential solution might be to use the Diffie-Hellman keys - that are
used in IKEv2 and HIP to setup a secure unicast link - for group
Diffie-Hellman key-negotiations. However, Diffie-Hellman is a
relatively heavy solution, especially if the group is large.
Symmetric and asymmetric keys can be used in group communication.
Asymmetric keys have the advantage that they can provide source
authentication. However, doing broadcast encryption with a single
public/private key pair is also not feasible. Although a single
symmetric key can be used to encrypt the communication or compute a
message authentication code, it has inherent risks since the capture
of a single node can compromise the key shared throughout the
network. The usage of symmetric-keys also does not provide source
authentication. Another factor to consider is that asymmetric
cryptography is more resource-intensive than symmetric key solutions.
Thus, the security risks and performance trade-offs of applying
either symmetric or asymmetric keys to a given IoT use case need to
be well-analyzed according to risk and usability assessments.
[ID-multicast] is looking at a combination of symmetric (for
encryption) and asymmetric (for authentication) in the same packet.
Conceptually, solutions that provide secure group communication at
the network layer (IPsec/IKEv2, HIP/Diet HIP) may have an advantage
in terms of the cryptographic overhead when compared to application-
focused security solutions (TLS/ DTLS). This is due to the fact that
application-focused solutions require cryptographic operations per
group application, whereas network layer approaches may allow sharing
secure group associations between multiple applications (for example,
for neighbor discovery and routing or service discovery). Hence,
implementing shared features lower in the communication stack can
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avoid redundant security measures. However, it is important to note
that sharing security contexts among different applications involves
potential security threats, e.g., if one of the applications is
malicious and monitors exchanged messages or injects fake messages.
In the case of OSCORE, it provides security for CoAP group
communication as defined in RFC7390, i.e., based on multicast IP. If
the same security association is reused for each application, then
this solution does not seem to have more cryptographic overhead
compared to IPsec.
Several group key solutions have been developed by the MSEC working
group [WG-MSEC] of the IETF. The MIKEY architecture [RFC4738] is one
example. While these solutions are specifically tailored for
multicast and group broadcast applications in the Internet, they
should also be considered as candidate solutions for group key
agreement in IoT. The MIKEY architecture for example describes a
coordinator entity that disseminates symmetric keys over pair-wise
end-to-end secured channels. However, such a centralized approach
may not be applicable in a distributed IoT environment, where the
choice of one or several coordinators and the management of the group
key is not trivial.
5.3.2. Mobility and IP Network Dynamics
It is expected that many things (for example, wearable sensors, and
user devices) will be mobile in the sense that they are attached to
different networks during the lifetime of a security association.
Built-in mobility signaling can greatly reduce the overhead of the
cryptographic protocols because unnecessary and costly re-
establishments of the session (possibly including handshake and key
agreement) can be avoided. IKEv2 supports host mobility with the
MOBIKE [RFC4555] and [RFC4621] extension. MOBIKE refrains from
applying heavyweight cryptographic extensions for mobility. However,
MOBIKE mandates the use of IPsec tunnel mode which requires the
transmission of an additional IP header in each packet.
HIP offers a simple yet effective mobility management by allowing
hosts to signal changes to their associations [RFC8046]. However,
slight adjustments might be necessary to reduce the cryptographic
costs, for example, by making the public-key signatures in the
mobility messages optional. Diet HIP does not define mobility yet
but it is sufficiently similar to HIP and can use the same
mechanisms. DTLS provides some mobility support by relying on a
connection ID (CID). The use of connection IDs can provide all the
mobility functionality described in [ID-Williams], except, sending
the updated location. The specific need for IP-layer mobility mainly
depends on the scenario in which the nodes operate. In many cases,
mobility supported by means of a mobile gateway may suffice to enable
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mobile IoT networks, such as body sensor networks. Using message
based application-layer security solutions such as OSCORE [ID-OSCORE]
can also alleviate the problem of re-establishing lower-layer
sessions for mobile nodes.
5.4. Secure software update and cryptographic agility
IoT devices are often expected to stay functional for several years
and decades even though they might operate unattended with direct
Internet connectivity. Software updates for IoT devices are
therefore not only required for new functionality, but also to
eliminate security vulnerabilities due to software bugs, design
flaws, or deprecated algorithms. Software bugs might remain even
after careful code review. Implementations of security protocols
might contain (design) flaws. Cryptographic algorithms can also
become insecure due to advances in cryptanalysis. Therefore, it is
necessary that devices which are incapable of verifying a
cryptographic signature are not exposed to the Internet (even
indirectly).
Schneier [SchneierSecurity] in his essay highlights several
challenges that hinder mechanisms for secure software update of IoT
devices. First, there is a lack of incentives for manufactures,
vendors and others on the supply chain to issue updates for their
devices. Second, parts of the software running on IoT devices is
simply a binary blob without any source code available. Since the
complete source code is not available, no patches can be written for
that piece of code. Lastly Schneier points out that even when
updates are available, users generally have to manually download and
install them. However, users are never alerted about security
updates and at many times do not have the necessary expertise to
manually administer the required updates.
The FTC staff report on Internet of Things - Privacy & Security in a
Connected World [FTCreport] and the Article 29 Working Party Opinion
8/2014 on the Recent Developments on the Internet of Things
[Article29] also document the challenges for secure remote software
update of IoT devices. They note that even providing such a software
update capability may add new vulnerabilities for constrained
devices. For example, a buffer overflow vulnerability in the
implementation of a software update protocol (TR69) [TR69] and an
expired certificate in a hub device [wink] demonstrate how the
software update process itself can introduce vulnerabilities.
Powerful IoT devices that run general purpose operating systems can
make use of sophisticated software update mechanisms known from the
desktop world. However, resource-constrained devices typically do
not have any operating system and are often not equipped with a
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memory management unit or similar tools. Therefore, they might
require more specialized solutions.
An important requirement for secure software and firmware updates is
source authentication. Source authentication requires the resource-
constrained things to implement public-key signature verification
algorithms. As stated in Section 5.1.1, resource-constrained things
have limited amount of computational capabilities and energy supply
available which can hinder the amount and frequency of cryptographic
processing that they can perform. In addition to source
authentication, software updates might require confidential delivery
over a secure (encrypted) channel. The complexity of broadcast
encryption can force the usage of point-to-point secure links -
however, this increases the duration of a software update in a large
system. Alternatively, it may force the usage of solutions in which
the software update is delivered to a gateway, and then distributed
to the rest of the system with a network key. Sending large amounts
of data that later needs to be assembled and verified over a secure
channel can consume a lot of energy and computational resources.
Correct scheduling of the software updates is also a crucial design
challenge. For example, a user of connected light bulbs would not
want them to update and restart at night. More importantly, the user
would not want all the lights to update at the same time.
Software updates in IoT systems are also needed to update old and
insecure cryptographic primitives. However, many IoT systems, some
of which are already deployed, are not designed with provisions for
cryptographic agility. For example, many devices come with a
wireless radio that has an AES128 hardware co-processor. These
devices solely rely on the co-processor for encrypting and
authenticating messages. A software update adding support for new
cryptographic algorithms implemented solely in software might not fit
on these devices due to limited memory, or might drastically hinder
its operational performance. This can lead to the use of old and
insecure software. Therefore, it is important to account for the
fact that cryptographic algorithms would need to be updated and
consider the following when planning for cryptographic agility:
1. Would it be secure to use the existing cryptographic algorithms
available on the device for updating with new cryptographic
algorithms that are more secure?
2. Will the new software-based implementation fit on the device
given the limited resources?
3. Would the normal operation of existing IoT applications on the
device be severely hindered by the update?
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Finally, we would like to highlight the previous and ongoing work in
the area of secure software and firmware updates at the IETF.
[RFC4108] describes how Cryptographic Message Syntax (CMS) [RFC5652]
can be used to protect firmware packages. The IAB has also organized
a workshop to understand the challenges for secure software update of
IoT devices. A summary of the recommendations to the standards
community derived from the discussions during that workshop have been
documented [RFC8240]. A working group called Software Updates for
Internet of Things (suit) [WG-SUIT] is currently working on a new
version [RFC4108] to reflect the best current practices for firmware
update based on experience from IoT deployments. It is specifically
working on describing an IoT firmware update architecture and
specifying a manifest format that contains meta-data about the
firmware update package. Finally, the Trusted Execution Environment
Provisioning working group [WG-TEEP] aims at developing a protocol
for lifecycle management of trusted applications running on the
secure area of a processor (Trusted Execution Enviornment (TEE)).
5.5. End-of-Life
Like all commercial devices, IoT devices have a given useful
lifetime. The term end-of-life (EOL) is used by vendors or network
operators to indicate the point of time in which they limit or end
support for the IoT device. This may be planned or unplanned (for
example when the manufacturer goes bankrupt, when the vendor just
decides to abandon a product, or when a network operator moves to a
different type of networking technology). A user should still be
able to use and perhaps even update the device. This requires for
some form of authorization handover.
Although this may seem far-fetched given the commercial interests and
market dynamics, we have examples from the mobile world where the
devices have been functional and up-to-date long after the original
vendor stopped supporting the device. CyanogenMod for Android
devices, and OpenWrt for home routers are two such instances where
users have been able to use and update their devices even after the
official EOL. Admittedly it is not easy for an average user to
install and configure their devices on their own. With the
deployment of millions of IoT devices, simpler mechanisms are needed
to allow users to add new root-of-trusts and install software and
firmware from other sources once the device is EOL.
5.6. Verifying device behavior
Users using new IoT appliances such as Internet-connected smart
televisions, speakers and cameras are often unaware that these
devices can undermine their privacy. Recent revelations have shown
that many IoT device vendors have been collecting sensitive private
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data through these connected appliances with or without appropriate
user warnings [cctv].
An IoT device user/owner would like to monitor and verify its
operational behavior. For instance, the user might want to know if
the device is connecting to the server of the manufacturer for any
reason. This feature - connecting to the manufacturer's server - may
be necessary in some scenarios, such as during the initial
configuration of the device. However, the user should be kept aware
of the data that the device is sending back to the vendor. For
example, the user might want to know if his/her TV is sending data
when he/she inserts a new USB stick.
Providing such information to the users in an understandable fashion
is challenging. This is because IoT devices are not only resource-
constrained in terms of their computational capability, but also in
terms of the user interface available. Also, the network
infrastructure where these devices are deployed will vary
significantly from one user environment to another. Therefore, where
and how this monitoring feature is implemented still remains an open
question.
Manufacturer Usage Description (MUD) files [ID-MUD] are perhaps a
first step towards implementation of such a monitoring service. The
idea behind MUD files is relatively simple: IoT devices would
disclose the location of their MUD file to the network during
installation. The network can then retrieve those files, and learn
about the intended behavior of the devices stated by the device
manufacturer. A network monitoring service could then warn the user/
owner of devices if they don't behave as expected.
Many devices and software services that automatically learn and
monitor the behavior of different IoT devices in a given network are
commercially available. Such monitoring devices/services can be
configured by the user to limit network traffic and trigger alarms
when unexpected operation of IoT devices is detected.
5.7. Testing: bug hunting and vulnerabilities
Given that IoT devices often have inadvertent vulnerabilities, both
users and developers would want to perform extensive testing on their
IoT devices, networks, and systems. Nonetheless, since the devices
are resource-constrained and manufactured by multiple vendors, some
of them very small, devices might be shipped with very limited
testing, so that bugs can remain and can be exploited at a later
stage. This leads to two main types of challenges:
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1. It remains to be seen how the software testing and quality
assurance mechanisms used from the desktop and mobile world will
be applied to IoT devices to give end users the confidence that
the purchased devices are robust. Bodies such as the European
Cyber Security Organization (ECSO) [ECSO] are working on
processes for security certification of IoT devices.
2. It is also an open question how the combination of devices from
multiple vendors might actually lead to dangerous network
configurations. For example, if combination of specific devices
can trigger unexpected behavior. It is needless to say that the
security of the whole system is limited by its weakest point.
5.8. Quantum-resistance
Many IoT systems that are being deployed today will remain
operational for many years. With the advancements made in the field
of quantum computers, it is possible that large-scale quantum
computers are available in the future for performing cryptanalysis on
existing cryptographic algorithms and cipher suites. If this
happens, it will have two consequences. First, functionalities
enabled by means of primitives such as RSA or ECC - namely key
exchange, public-key encryption and signature - would not be secure
anymore due to Shor's algorithm. Second, the security level of
symmetric algorithms will decrease, for example, the security of a
block cipher with a key size of b bits will only offer b/2 bits of
security due to Grover's algorithm.
The above scenario becomes more urgent when we consider the so called
"harvest and decrypt" attack in which an attacker can start to
harvest (store) encrypted data today, before a quantum-computer is
available, and decrypt it years later, once a quantum computer is
available. Such "harvest and decrypt" attacks are not new and were
used in the Venona project [venona-project]. Many IoT devices that
are being deployed today will remain operational for a decade or even
longer. During this time, digital signatures used to sign software
updates might become obsolete making the secure update of IoT devices
challenging.
This situation would require us to move to quantum-resistant
alternatives, in particular, for those functionalities involving key
exchange, public-key encryption and signatures. [ID-c2pq] describes
when quantum computers may become widely available and what steps are
necessary for transition to cryptographic algorithms that provide
security even in presence of quantum computers. While future
planning is hard, it may be a necessity in certain critical IoT
deployments which are expected to last decades or more. Although
increasing the key-size of the different algorithms is definitely an
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option, it would also incur additional computational overhead and
network traffic. This would be undesirable in most scenarios. There
have been recent advancements in quantum-resistant cryptography. We
refer to [ETSI-GR-QSC-001] for an extensive overview of existing
quantum-resistant cryptography and [RFC7696] provides guidelines for
cryptographic algorithm agility.
5.9. Privacy protection
People will eventually be surrounded by hundreds of connected IoT
devices. Even if the communication links are encrypted and
protected, information about people might still be collected or
processed for different purposes. The fact that IoT devices in the
vicinity of people might enable more pervasive monitoring can
negatively impact their privacy. For instance, imagine the scenario
where a static presence sensor emits a packet due to the presence or
absence of people in its vicinity. In such a scenario, anyone who
can observe the packet, can gather critical privacy-sensitive
information.
Such information about people is referred to as personal data in the
European Union (EU) or Personally identifiable information (PII) in
the United States (US), In particular, the General Data Protection
Regulation (GDPR) [GDPR] defines personal data as: 'any information
relating to an identified or identifiable natural person ('data
subject'); an identifiable natural person is one who can be
identified, directly or indirectly, in particular by reference to an
identifier such as a name, an identification number, location data,
an online identifier or to one or more factors specific to the
physical, physiological, genetic, mental, economic, cultural or
social identity of that natural person'.
Ziegeldorf [Ziegeldorf] defines privacy in IoT as a threefold
guarantee:
1. Awareness of the privacy risks imposed by IoT devices and
services. This awareness is achieved by means of transparent
practices by the data controller, i.e., the entity that is
providing IoT devices and/or services.
2. Individual control over the collection and processing of personal
information by IoT devices and services.
3. Awareness and control of the subsequent use and dissemination of
personal information by data controllers to any entity outside
the subject's personal control sphere. This point implies that
the data controller must be accountable for its actions on the
personal information.
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Based on this definition, several threats to the privacy of users
have been documented [Ziegeldorf] and [RFC6973], in particular
considering the IoT environment and its lifecycle:
1. Identification - refers to the identification of the users, their
IoT devices, and generated data.
2. Localization - relates to the capability of locating a user and
even tracking them, e.g., by tracking MAC addresses in Wi-Fi or
Bluetooth.
3. Profiling - is about creating a profile of the user and their
preferences.
4. Interaction - occurs when a user has been profiled and a given
interaction is preferred, presenting (for example, visually) some
information that discloses private information.
5. Lifecycle transitions - take place when devices are, for example,
sold without properly removing private data.
6. Inventory attacks - happen if specific information about IoT
devices in possession of a user is disclosed.
7. Linkage - is about when information of two of more IoT systems
(or other data sets) is combined so that a broader view of the
personal data captured can be created.
When IoT systems are deployed, the above issues should be considered
to ensure that private data remains private. These issues are
particularly challenging in environments in which multiple users with
different privacy preferences interact with the same IoT devices.
For example, an IoT device controlled by user A (low privacy
settings) might leak private information about another user B (high
privacy settings). How to deal with these threats in practice is an
area of ongoing research.
5.10. Reverse engineering considerations
Many IoT devices are resource-constrained and often deployed in
unattended environments. Some of these devices can also be purchased
off-the-shelf or online without any credential-provisioning process.
Therefore, an attacker can have direct access to the device and apply
advanced techniques to retrieve information that a traditional black
box model does not consider. Example of those techniques are side-
channel attacks or code disassembly. By doing this, the attacker can
try to retrieve data such as:
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1. long term keys. These long term keys can be extracted by means
of a side-channel attack or reverse engineering. If these keys
are exposed, then they might be used to perform attacks on
devices deployed in other locations.
2. source code. Extraction of source code might allow the attacker
to determine bugs or find exploits to perform other types of
attacks. The attacker might also just sell the source code.
3. proprietary algorithms. The attacker can analyze these
algorithms gaining valuable know-how. The attacker can also
create copies of the product (based on those proprietary
algorithms) or modify the algorithms to perform more advanced
attacks.
4. configuration or personal data. The attacker might be able to
read personal data, e.g., healthcare data, that has been stored
on a device.
One existing solution to prevent such data leaks is the use of a
secure element, a tamper-resistant device that is capable of securely
hosting applications and their confidential data. Another potential
solution is the usage of of Physical Unclonable Function (PUFs) that
serves as unique digital fingerprint of a hardware device. PUFs can
also enable other functionalities such as secure key storage.
Protection against such data leakage patterns is non-trivial since
devices are inherently resource-constrained. An open question is
whether there are any viable techniques to protect IoT devices and
the data in the devices in such an adversarial model.
5.11. Trustworthy IoT Operation
Flaws in the design and implementation of IoT devices and networks
can lead to security vulnerabilities. A common flaw is the use of
well-known or easy-to-guess passwords for configuration of IoT
devices. Many such compromised IoT devices can be found on the
Internet by means of tools such as Shodan [shodan]. Once discovered,
these compromised devices can be exploited at scale, for example, to
launch DDoS attacks. Dyn, a major DNS , was attacked by means of a
DDoS attack originating from a large IoT botnet composed of thousands
of compromised IP-cameras [dyn-attack]. There are several open
research questions in this area:
1. How to avoid vulnerabilities in IoT devices that can lead to
large-scale attacks?
2. How to detect sophisticated attacks against IoT devices?
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3. How to prevent attackers from exploiting known vulnerabilities at
a large scale?
Some ideas are being explored to address this issue. One of the
approaches relies on the use of Manufacturer Usage Description (MUD)
files [ID-MUD]. As explained earlier, this proposal requires IoT
devices to disclose the location of their MUD file to the network
during installation. The network can then (i) retrieve those files,
(ii) learn from the manufacturers the intended usage of the devices,
for example, which services they need to access, and then (iii)
create suitable filters and firewall rules.
6. Conclusions and Next Steps
This Internet Draft provides IoT security researchers, system
designers and implementers with an overview of security requirements
in the IP-based Internet of Things. We discuss the security threats,
state-of-the-art, and challenges.
Although plenty of steps have been realized during the last few years
(summarized in Section 4.1) and many organizations are publishing
general recommendations (Section 4.3) describing how IoT should be
secured, there are many challenges ahead that require further
attention. Challenges of particular importance are bootstrapping of
security, group security, secure software updates, long-term security
and quantum-resistance, privacy protection, data leakage prevention -
where data could be cryptographic keys, personal data, or even
algorithms - and ensuring trustworthy IoT operation.
Authors of new IoT specifications and implementors need to consider
how all the security challenges discussed in this draft (and those
that emerge later) affect their work. The authors of IoT
specifications not only need to put in a real effort towards
addressing the security challenges, but also clearly documenting how
the security challenges are addressed. This would reduce the chances
of security vulnerabilities in the code written by implementors of
those specifications.
7. Security Considerations
This entire memo deals with security issues.
8. IANA Considerations
This document contains no request to IANA.
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9. Acknowledgments
We gratefully acknowledge feedback and fruitful discussion with
Tobias Heer, Robert Moskowitz, Thorsten Dahm, Hannes Tschofenig,
Carsten Bormann, Barry Raveendran, Ari Keranen, Goran Selander, Fred
Baker, Vicent Roca, Thomas Fossati and Eliot Lear. We acknowledge
the additional authors of the previous version of this document Sye
Loong Keoh, Rene Hummen and Rene Struik.
10. Informative References
[Article29]
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[BACNET] "BACnet", Web http://www.bacnet.org/, February 2011.
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[cctv] "Backdoor In MVPower DVR Firmware Sends CCTV Stills To an
Email Address In China", Web
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[DCMS] "Secure by Design: Improving the cyber security of
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[DHS] "Strategic Principles For Securing the Internet of Things
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[dyn-attack]
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[ecc25519]
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[Fairhair]
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[GDPR] "The EU General Data Protection Regulation",
Web https://www.eugdpr.org/, n.d..
[GSMAsecurity]
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networks/iot-security-guidelines/, n.d..
[ID-6lonfc]
Choi, Y., Hong, Y., Youn, J., Kim, D., and J. Choi,
"Transmission of IPv6 Packets over Near Field
Communication", draft-ietf-6lo-nfc-12 (work in progress),
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[ID-6tisch]
Thubert, P., "An Architecture for IPv6 over the TSCH mode
of IEEE 802.15.4", draft-ietf-6tisch-architecture-18 (work
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[ID-acedtls]
Gerdes, S., Bergmann, O., Bormann, C., Selander, G., and
L. Seitz, "Datagram Transport Layer Security (DTLS)
Profile for Authentication and Authorization for
Constrained Environments (ACE)", draft-ietf-ace-dtls-
authorize-05 (work in progress), October 2018.
[ID-aceoauth]
Seitz, L., Selander, G., Wahlstroem, E., Erdtman, S., and
H. Tschofenig, "Authentication and Authorization for
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(work in progress), November 2018.
[ID-bootstrap]
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[ID-Daniel]
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[ID-dietesp]
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[ID-HIP-DEX]
Moskowitz, R., "HIP Diet EXchange (DEX)", draft-moskowitz-
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[ID-Moore]
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[ID-MUD] Lear, E., Droms, R., and D. Romascanu, "Manufacturer Usage
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[ID-multicast]
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[IoTSecFoundation]
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[IPSO] "IPSO Alliance", Web http://www.ipso-alliance.org, n.d..
[ISOC-OTA]
"Internet Society's Online Trust Alliance (OTA)",
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[lora] "LoRa - Wide Area Networks for IoT", Web https://www.lora-
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[LWM2M] "OMA LWM2M", Web
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[mirai] Kolias, C., Kambourakis, G., Stavrou, A., and J. Voas,,
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[nbiot] "NarrowBand IoT", Web
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[NIST-Guide]
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[nist-lightweight-project]
"NIST lightweight Project", Web www.nist.gov/programs-
projects/lightweight-cryptography,
www.nist.gov/sites/default/files/documents/2016/10/17/
sonmez-turan-presentation-lwc2016.pdf, n.d..
[NISTSP800-122]
Erika McCallister, ., Tim Grance, ., and . Karen Scarfone,
"NIST SP800-122 - Guide to Protecting the Confidentiality
of Personally Identifiable Information", Web
https://nvlpubs.nist.gov/nistpubs/legacy/sp/
nistspecialpublication800-122.pdf, n.d..
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[NISTSP800-30r1]
"NIST SP 800-30r1 - Guide for Conducting Risk
Assessments", Web
https://nvlpubs.nist.gov/nistpubs/Legacy/SP/
nistspecialpublication800-30r1.pdf, n.d..
[NISTSP800-34r1]
Marianne Swanson, ., Pauline Bowen, ., Amy Wohl Phillips,
., Dean Gallup, ., and . David Lynes, "NIST SP800-34r1 -
Contingency Planning Guide for Federal Information
Systems", Web https://nvlpubs.nist.gov/nistpubs/Legacy/SP/
nistspecialpublication800-34r1.pdf, n.d..
[OCF] "Open Connectivity Foundation",
Web https://openconnectivity.org/, n.d..
[OneM2M] "OneM2M", Web http://www.onem2m.org/, n.d..
[OWASP] "IoT Security Guidance",
Web https://www.owasp.org/index.php/IoT_Security_Guidance,
n.d..
[RFC2818] Rescorla, E., "HTTP Over TLS", RFC 2818,
DOI 10.17487/RFC2818, May 2000,
<https://www.rfc-editor.org/info/rfc2818>.
[RFC3748] Aboba, B., Blunk, L., Vollbrecht, J., Carlson, J., and H.
Levkowetz, Ed., "Extensible Authentication Protocol
(EAP)", RFC 3748, DOI 10.17487/RFC3748, June 2004,
<https://www.rfc-editor.org/info/rfc3748>.
[RFC3756] Nikander, P., Ed., Kempf, J., and E. Nordmark, "IPv6
Neighbor Discovery (ND) Trust Models and Threats",
RFC 3756, DOI 10.17487/RFC3756, May 2004,
<https://www.rfc-editor.org/info/rfc3756>.
[RFC3833] Atkins, D. and R. Austein, "Threat Analysis of the Domain
Name System (DNS)", RFC 3833, DOI 10.17487/RFC3833, August
2004, <https://www.rfc-editor.org/info/rfc3833>.
[RFC4016] Parthasarathy, M., "Protocol for Carrying Authentication
and Network Access (PANA) Threat Analysis and Security
Requirements", RFC 4016, DOI 10.17487/RFC4016, March 2005,
<https://www.rfc-editor.org/info/rfc4016>.
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[RFC4108] Housley, R., "Using Cryptographic Message Syntax (CMS) to
Protect Firmware Packages", RFC 4108,
DOI 10.17487/RFC4108, August 2005,
<https://www.rfc-editor.org/info/rfc4108>.
[RFC4120] Neuman, C., Yu, T., Hartman, S., and K. Raeburn, "The
Kerberos Network Authentication Service (V5)", RFC 4120,
DOI 10.17487/RFC4120, July 2005,
<https://www.rfc-editor.org/info/rfc4120>.
[RFC4422] Melnikov, A., Ed. and K. Zeilenga, Ed., "Simple
Authentication and Security Layer (SASL)", RFC 4422,
DOI 10.17487/RFC4422, June 2006,
<https://www.rfc-editor.org/info/rfc4422>.
[RFC4555] Eronen, P., "IKEv2 Mobility and Multihoming Protocol
(MOBIKE)", RFC 4555, DOI 10.17487/RFC4555, June 2006,
<https://www.rfc-editor.org/info/rfc4555>.
[RFC4621] Kivinen, T. and H. Tschofenig, "Design of the IKEv2
Mobility and Multihoming (MOBIKE) Protocol", RFC 4621,
DOI 10.17487/RFC4621, August 2006,
<https://www.rfc-editor.org/info/rfc4621>.
[RFC4738] Ignjatic, D., Dondeti, L., Audet, F., and P. Lin, "MIKEY-
RSA-R: An Additional Mode of Key Distribution in
Multimedia Internet KEYing (MIKEY)", RFC 4738,
DOI 10.17487/RFC4738, November 2006,
<https://www.rfc-editor.org/info/rfc4738>.
[RFC4919] Kushalnagar, N., Montenegro, G., and C. Schumacher, "IPv6
over Low-Power Wireless Personal Area Networks (6LoWPANs):
Overview, Assumptions, Problem Statement, and Goals",
RFC 4919, DOI 10.17487/RFC4919, August 2007,
<https://www.rfc-editor.org/info/rfc4919>.
[RFC4944] Montenegro, G., Kushalnagar, N., Hui, J., and D. Culler,
"Transmission of IPv6 Packets over IEEE 802.15.4
Networks", RFC 4944, DOI 10.17487/RFC4944, September 2007,
<https://www.rfc-editor.org/info/rfc4944>.
[RFC5191] Forsberg, D., Ohba, Y., Ed., Patil, B., Tschofenig, H.,
and A. Yegin, "Protocol for Carrying Authentication for
Network Access (PANA)", RFC 5191, DOI 10.17487/RFC5191,
May 2008, <https://www.rfc-editor.org/info/rfc5191>.
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[RFC5652] Housley, R., "Cryptographic Message Syntax (CMS)", STD 70,
RFC 5652, DOI 10.17487/RFC5652, September 2009,
<https://www.rfc-editor.org/info/rfc5652>.
[RFC5713] Moustafa, H., Tschofenig, H., and S. De Cnodder, "Security
Threats and Security Requirements for the Access Node
Control Protocol (ANCP)", RFC 5713, DOI 10.17487/RFC5713,
January 2010, <https://www.rfc-editor.org/info/rfc5713>.
[RFC5903] Fu, D. and J. Solinas, "Elliptic Curve Groups modulo a
Prime (ECP Groups) for IKE and IKEv2", RFC 5903,
DOI 10.17487/RFC5903, June 2010,
<https://www.rfc-editor.org/info/rfc5903>.
[RFC6272] Baker, F. and D. Meyer, "Internet Protocols for the Smart
Grid", RFC 6272, DOI 10.17487/RFC6272, June 2011,
<https://www.rfc-editor.org/info/rfc6272>.
[RFC6347] Rescorla, E. and N. Modadugu, "Datagram Transport Layer
Security Version 1.2", RFC 6347, DOI 10.17487/RFC6347,
January 2012, <https://www.rfc-editor.org/info/rfc6347>.
[RFC6550] Winter, T., Ed., Thubert, P., Ed., Brandt, A., Hui, J.,
Kelsey, R., Levis, P., Pister, K., Struik, R., Vasseur,
JP., and R. Alexander, "RPL: IPv6 Routing Protocol for
Low-Power and Lossy Networks", RFC 6550,
DOI 10.17487/RFC6550, March 2012,
<https://www.rfc-editor.org/info/rfc6550>.
[RFC6551] Vasseur, JP., Ed., Kim, M., Ed., Pister, K., Dejean, N.,
and D. Barthel, "Routing Metrics Used for Path Calculation
in Low-Power and Lossy Networks", RFC 6551,
DOI 10.17487/RFC6551, March 2012,
<https://www.rfc-editor.org/info/rfc6551>.
[RFC6568] Kim, E., Kaspar, D., and JP. Vasseur, "Design and
Application Spaces for IPv6 over Low-Power Wireless
Personal Area Networks (6LoWPANs)", RFC 6568,
DOI 10.17487/RFC6568, April 2012,
<https://www.rfc-editor.org/info/rfc6568>.
[RFC6690] Shelby, Z., "Constrained RESTful Environments (CoRE) Link
Format", RFC 6690, DOI 10.17487/RFC6690, August 2012,
<https://www.rfc-editor.org/info/rfc6690>.
[RFC6749] Hardt, D., Ed., "The OAuth 2.0 Authorization Framework",
RFC 6749, DOI 10.17487/RFC6749, October 2012,
<https://www.rfc-editor.org/info/rfc6749>.
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[RFC6973] Cooper, A., Tschofenig, H., Aboba, B., Peterson, J.,
Morris, J., Hansen, M., and R. Smith, "Privacy
Considerations for Internet Protocols", RFC 6973,
DOI 10.17487/RFC6973, July 2013,
<https://www.rfc-editor.org/info/rfc6973>.
[RFC7049] Bormann, C. and P. Hoffman, "Concise Binary Object
Representation (CBOR)", RFC 7049, DOI 10.17487/RFC7049,
October 2013, <https://www.rfc-editor.org/info/rfc7049>.
[RFC7228] Bormann, C., Ersue, M., and A. Keranen, "Terminology for
Constrained-Node Networks", RFC 7228,
DOI 10.17487/RFC7228, May 2014,
<https://www.rfc-editor.org/info/rfc7228>.
[RFC7252] Shelby, Z., Hartke, K., and C. Bormann, "The Constrained
Application Protocol (CoAP)", RFC 7252,
DOI 10.17487/RFC7252, June 2014,
<https://www.rfc-editor.org/info/rfc7252>.
[RFC7296] Kaufman, C., Hoffman, P., Nir, Y., Eronen, P., and T.
Kivinen, "Internet Key Exchange Protocol Version 2
(IKEv2)", STD 79, RFC 7296, DOI 10.17487/RFC7296, October
2014, <https://www.rfc-editor.org/info/rfc7296>.
[RFC7401] Moskowitz, R., Ed., Heer, T., Jokela, P., and T.
Henderson, "Host Identity Protocol Version 2 (HIPv2)",
RFC 7401, DOI 10.17487/RFC7401, April 2015,
<https://www.rfc-editor.org/info/rfc7401>.
[RFC7515] Jones, M., Bradley, J., and N. Sakimura, "JSON Web
Signature (JWS)", RFC 7515, DOI 10.17487/RFC7515, May
2015, <https://www.rfc-editor.org/info/rfc7515>.
[RFC7516] Jones, M. and J. Hildebrand, "JSON Web Encryption (JWE)",
RFC 7516, DOI 10.17487/RFC7516, May 2015,
<https://www.rfc-editor.org/info/rfc7516>.
[RFC7517] Jones, M., "JSON Web Key (JWK)", RFC 7517,
DOI 10.17487/RFC7517, May 2015,
<https://www.rfc-editor.org/info/rfc7517>.
[RFC7519] Jones, M., Bradley, J., and N. Sakimura, "JSON Web Token
(JWT)", RFC 7519, DOI 10.17487/RFC7519, May 2015,
<https://www.rfc-editor.org/info/rfc7519>.
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[RFC7520] Miller, M., "Examples of Protecting Content Using JSON
Object Signing and Encryption (JOSE)", RFC 7520,
DOI 10.17487/RFC7520, May 2015,
<https://www.rfc-editor.org/info/rfc7520>.
[RFC7668] Nieminen, J., Savolainen, T., Isomaki, M., Patil, B.,
Shelby, Z., and C. Gomez, "IPv6 over BLUETOOTH(R) Low
Energy", RFC 7668, DOI 10.17487/RFC7668, October 2015,
<https://www.rfc-editor.org/info/rfc7668>.
[RFC7696] Housley, R., "Guidelines for Cryptographic Algorithm
Agility and Selecting Mandatory-to-Implement Algorithms",
BCP 201, RFC 7696, DOI 10.17487/RFC7696, November 2015,
<https://www.rfc-editor.org/info/rfc7696>.
[RFC7744] Seitz, L., Ed., Gerdes, S., Ed., Selander, G., Mani, M.,
and S. Kumar, "Use Cases for Authentication and
Authorization in Constrained Environments", RFC 7744,
DOI 10.17487/RFC7744, January 2016,
<https://www.rfc-editor.org/info/rfc7744>.
[RFC7815] Kivinen, T., "Minimal Internet Key Exchange Version 2
(IKEv2) Initiator Implementation", RFC 7815,
DOI 10.17487/RFC7815, March 2016,
<https://www.rfc-editor.org/info/rfc7815>.
[RFC7925] Tschofenig, H., Ed. and T. Fossati, "Transport Layer
Security (TLS) / Datagram Transport Layer Security (DTLS)
Profiles for the Internet of Things", RFC 7925,
DOI 10.17487/RFC7925, July 2016,
<https://www.rfc-editor.org/info/rfc7925>.
[RFC8046] Henderson, T., Ed., Vogt, C., and J. Arkko, "Host Mobility
with the Host Identity Protocol", RFC 8046,
DOI 10.17487/RFC8046, February 2017,
<https://www.rfc-editor.org/info/rfc8046>.
[RFC8105] Mariager, P., Petersen, J., Ed., Shelby, Z., Van de Logt,
M., and D. Barthel, "Transmission of IPv6 Packets over
Digital Enhanced Cordless Telecommunications (DECT) Ultra
Low Energy (ULE)", RFC 8105, DOI 10.17487/RFC8105, May
2017, <https://www.rfc-editor.org/info/rfc8105>.
[RFC8152] Schaad, J., "CBOR Object Signing and Encryption (COSE)",
RFC 8152, DOI 10.17487/RFC8152, July 2017,
<https://www.rfc-editor.org/info/rfc8152>.
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[RFC8240] Tschofenig, H. and S. Farrell, "Report from the Internet
of Things Software Update (IoTSU) Workshop 2016",
RFC 8240, DOI 10.17487/RFC8240, September 2017,
<https://www.rfc-editor.org/info/rfc8240>.
[RFC8259] Bray, T., Ed., "The JavaScript Object Notation (JSON) Data
Interchange Format", STD 90, RFC 8259,
DOI 10.17487/RFC8259, December 2017,
<https://www.rfc-editor.org/info/rfc8259>.
[RFC8376] Farrell, S., Ed., "Low-Power Wide Area Network (LPWAN)
Overview", RFC 8376, DOI 10.17487/RFC8376, May 2018,
<https://www.rfc-editor.org/info/rfc8376>.
[RFC8428] Jennings, C., Shelby, Z., Arkko, J., Keranen, A., and C.
Bormann, "Sensor Measurement Lists (SenML)", RFC 8428,
DOI 10.17487/RFC8428, August 2018,
<https://www.rfc-editor.org/info/rfc8428>.
[RFC8446] Rescorla, E., "The Transport Layer Security (TLS) Protocol
Version 1.3", RFC 8446, DOI 10.17487/RFC8446, August 2018,
<https://www.rfc-editor.org/info/rfc8446>.
[RG-T2TRG]
"IRTF Thing-to-Thing (T2TRG) Research Group",
Web https://datatracker.ietf.org/rg/t2trg/charter/, n.d..
[SchneierSecurity]
"The Internet of Things Is Wildly Insecure--And Often
Unpatchable", Web
https://www.schneier.com/essays/archives/2014/01/
the_internet_of_thin.html, n.d..
[SEAL] "Simple Encrypted Arithmetic Library - SEAL", Web
https://www.microsoft.com/en-
us/research/publication/simple-encrypted-arithmetic-
library-seal-v2-0/, n.d..
[shodan] "Shodan", Web https://www.shodan.io/, n.d..
[sigfox] "Sigfox - The Global Communications Service Provider for
the Internet of Things (IoT)",
Web https://www.sigfox.com/, n.d..
[Thread] "Thread Group", Web http://threadgroup.org/, n.d..
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[TR69] "Too Many Cooks - Exploiting the Internet-of-TR-
069-Things", Web https://media.ccc.de/v/31c3_-_6166_-_en_-
_saal_6_-_201412282145_-_too_many_cooks_-
_exploiting_the_internet-of-tr-069-things_-
_lior_oppenheim_-_shahar_tal, n.d..
[venona-project]
"Venona Project", Web https://www.nsa.gov/news-
features/declassified-documents/venona/index.shtml, n.d..
[WG-6lo] "IETF IPv6 over Networks of Resource-constrained Nodes
(6lo) Working Group",
Web https://datatracker.ietf.org/wg/6lo/charter/, n.d..
[WG-6LoWPAN]
"IETF IPv6 over Low power WPAN (6lowpan) Working Group",
Web http://tools.ietf.org/wg/6lowpan/, n.d..
[WG-ACE] "IETF Authentication and Authorization for Constrained
Environments (ACE) Working Group",
Web https://datatracker.ietf.org/wg/ace/charter/, n.d..
[WG-ACME] "Automated Certificate Management Environment Working
Group", Web https://datatracker.ietf.org/wg/acme/about/,
n.d..
[WG-CoRE] "IETF Constrained RESTful Environment (CoRE) Working
Group", Web https://datatracker.ietf.org/wg/core/charter/,
n.d..
[WG-LPWAN]
"IETF Low Power Wide-Area Networks Working Group",
Web https://datatracker.ietf.org/wg/lpwan/, n.d..
[WG-LWIG] "IETF Light-Weight Implementation Guidance (LWIG) Working
Group", Web https://datatracker.ietf.org/wg/lwig/charter/,
n.d..
[WG-MSEC] "IETF MSEC Working Group",
Web https://datatracker.ietf.org/wg/msec/, n.d..
[WG-SUIT] "IETF Software Updates for Internet of Things (suit)",
Web https://datatracker.ietf.org/group/suit/about/, n.d..
[WG-TEEP] "IETF Trusted Execution Environment Provisioning (teep)",
Web https://datatracker.ietf.org/wg/teep/about/, n.d..
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[wink] "Wink's Outage Shows Us How Frustrating Smart Homes Could
Be", Web http://www.wired.com/2015/04/smart-home-
headaches/, n.d..
[ZB] "ZigBee Alliance", Web http://www.zigbee.org/, February
2011.
[Ziegeldorf]
Ziegeldorf, J., Garcia-Morchon, O., and K. Wehrle,,
"Privacy in the Internet of Things: Threats and
Challenges", Security and Communication Networks - Special
Issue on Security in a Completely Interconnected World ,
2013.
Authors' Addresses
Oscar Garcia-Morchon
Philips IP&S
High Tech Campus 5
Eindhoven, 5656 AA
The Netherlands
Email: oscar.garcia-morchon@philips.com
Sandeep S. Kumar
Philips Research
High Tech Campus
Eindhoven, 5656 AA
The Netherlands
Email: sandeep.kumar@philips.com
Mohit Sethi
Ericsson
Hirsalantie 11
Jorvas, 02420
Finland
Email: mohit@piuha.net
Garcia-Morchon, et al. Expires June 16, 2019 [Page 47]
