Internet DRAFT - draft-ietf-lwig-crypto-sensors
draft-ietf-lwig-crypto-sensors
Light-Weight Implementation Guidance M. Sethi
Internet-Draft J. Arkko
Intended status: Informational A. Keranen
Expires: August 30, 2018 Ericsson
H. Back
Nokia
February 26, 2018
Practical Considerations and Implementation Experiences in Securing
Smart Object Networks
draft-ietf-lwig-crypto-sensors-06
Abstract
This memo describes challenges associated with securing resource-
constrained smart object devices. The memo describes a possible
deployment model where resource-constrained devices sign message
objects, discusses the availability of cryptographic libraries for
resource-constrained devices and presents some preliminary
experiences with those libraries for message signing on resource-
constrained devices. Lastly, the memo discusses trade-offs involving
different types of security approaches.
Status of This Memo
This Internet-Draft is submitted in full conformance with the
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This Internet-Draft will expire on August 30, 2018.
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
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Table of Contents
1. Introduction . . . . . . . . . . . . . . . . . . . . . . . . 2
2. Related Work . . . . . . . . . . . . . . . . . . . . . . . . 3
3. Challenges . . . . . . . . . . . . . . . . . . . . . . . . . 4
4. Proposed Deployment Model . . . . . . . . . . . . . . . . . . 6
4.1. Provisioning . . . . . . . . . . . . . . . . . . . . . . 6
4.2. Protocol Architecture . . . . . . . . . . . . . . . . . . 9
5. Code Availability . . . . . . . . . . . . . . . . . . . . . . 10
6. Implementation Experiences . . . . . . . . . . . . . . . . . 11
7. Example Application . . . . . . . . . . . . . . . . . . . . . 18
8. Design Trade-Offs . . . . . . . . . . . . . . . . . . . . . . 21
8.1. Feasibility . . . . . . . . . . . . . . . . . . . . . . . 21
8.2. Freshness . . . . . . . . . . . . . . . . . . . . . . . . 22
8.3. Layering . . . . . . . . . . . . . . . . . . . . . . . . 24
8.4. Symmetric vs. Asymmetric Crypto . . . . . . . . . . . . . 26
9. Summary . . . . . . . . . . . . . . . . . . . . . . . . . . . 27
10. Security Considerations . . . . . . . . . . . . . . . . . . . 27
11. IANA Considerations . . . . . . . . . . . . . . . . . . . . . 27
12. Informative references . . . . . . . . . . . . . . . . . . . 27
Appendix A. Acknowledgments . . . . . . . . . . . . . . . . . . 34
Authors' Addresses . . . . . . . . . . . . . . . . . . . . . . . 34
1. Introduction
This memo describes challenges associated with securing smart object
devices in constrained implementations and environments. In
Section 3 we specifically discuss three challenges: the
implementation difficulties encountered on resource-constrained
platforms, the problem of provisioning keys and making the choice of
implementing security at the appropriate layer.
Section 4 discusses a potential deployment model for constrained
environments. The model requires minimal amount of configuration,
and we believe it is a natural fit with the typical communication
practices in smart object networking environments.
Section 5 discusses the availability of cryptographic libraries.
Section 6 presents some experiences in implementing cryptography on
resource-constrained devices using those libraries, including
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information about achievable code sizes and speeds on typical
hardware.
Finally, Section 8 discusses trade-offs involving different types of
security approaches.
2. Related Work
Constrained Application Protocol (CoAP) [RFC7252] is a light-weight
protocol designed to be used in machine-to-machine applications such
as smart energy and building automation. Our discussion uses this
protocol as an example, but the conclusions may apply to other
similar protocols. The CoAP base specification [RFC7252] outlines
how to use DTLS [RFC6347] and IPsec [RFC4303] for securing the
protocol. DTLS can be applied with pairwise shared keys, raw public
keys or with certificates. The security model in all cases is mutual
authentication, so while there is some commonality to HTTP [RFC7230]
in verifying the server identity, in practice the models are quite
different. The use of IPsec with CoAP is described with regards to
the protocol requirements, noting that lightweight implementations of
IKEv2 exist [RFC7815]. However, the CoAP specification is silent on
policy and other aspects that are normally necessary in order to
implement interoperable use of IPsec in any environment [RFC5406].
[I-D.irtf-t2trg-iot-seccons] documents the different stages in the
lifecycle of a smart object. Next, it highlights the security
threats for smart objects and the challenges that one might face to
protect against these threats. The document also looks at various
security protocols available, including IKEv2/IPsec [RFC7296], TLS/
SSL [RFC5246], DTLS [RFC6347], HIP [RFC7401],
[I-D.moskowitz-hip-dex], PANA [RFC5191], and EAP [RFC3748]. Lastly,
[I-D.sarikaya-t2trg-sbootstrapping] discusses bootstrapping
mechanisms available for resource-constrained IoT devices.
[RFC6574] gives an overview of the security discussions at the March
2011 IAB workshop on smart objects. The workshop recommended that
additional work should be undertaken in developing suitable
credential management mechanisms (perhaps something similar to the
Bluetooth pairing mechanism), understanding the implementability of
standard security mechanisms in resource-constrained devices, and
additional research in the area of lightweight cryptographic
primitives.
[I-D.moskowitz-hip-dex] defines a light-weight version of the HIP
protocol for low-power nodes. This version uses a fixed set of
algorithms, Elliptic Curve Cryptography (ECC), and eliminates hash
functions. The protocol still operates based on host identities, and
runs end-to-end between hosts, protecting all IP layer
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communications. [RFC6078] describes an extension of HIP that can be
used to send upper layer protocol messages without running the usual
HIP base exchange at all.
[I-D.daniel-6lowpan-security-analysis] makes a comprehensive analysis
of security issues related to 6LoWPAN networks, but its findings also
apply more generally for all low-powered networks. Some of the
issues this document discusses include the need to minimize the
number of transmitted bits and simplify implementations, threats in
the smart object networking environments, and the suitability of
6LoWPAN security mechanisms, IPsec, and key management protocols for
implementation in these environments.
3. Challenges
This section discusses three challenges: 1) implementation
difficulties, 2) practical provisioning problems, 3) layering and
communication models.
One of the most often discussed issues in the security for the
Internet of Things relate to implementation difficulties. The desire
to build resource-constrained, battery-operated, and inexpensive
devices drives the creation of devices with a limited protocol and
application suite. Some of the typical limitations include running
CoAP instead of HTTP, limited support for security mechanisms,
limited processing power for long key lengths, sleep schedule that
does not allow communication at all times, and so on. In addition,
the devices typically have very limited support for configuration,
making it hard to set up secrets and trust anchors.
The implementation difficulties are important, but they should not be
overemphasized. It is important to select the right security
mechanisms and avoid duplicated or unnecessary functionality. But at
the end of the day, if strong cryptographic security is needed, the
implementations have to support that. It is important for developers
and product designers to determine what security threats they want to
tackle and the resulting security requirements before selecting the
hardware. Often, development work in the wild happens in the wrong
order: a particular platform with a resource-constrained
microcontroller is chosen first, and then the security features that
can fit on it are decided. Also, the use of the most lightweight
algorithms and cryptographic primitives is useful, but should not be
the only consideration in the design and development.
Interoperability is also important, and often other parts of the
system, such as key management protocols or certificate formats are
heavier to implement than the algorithms themselves.
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The second challenge relates to practical provisioning problems.
This is perhaps the most fundamental and difficult issue, and
unfortunately often neglected in the design. There are several
problems in the provisioning and management of smart object networks:
o Resource-constrained devices have no natural user interface for
configuration that would be required for the installation of
shared secrets and other security-related parameters. Typically,
there is no keyboard, no display, and there may not even be
buttons to press. Some devices may only have one interface, the
interface to the network.
o Manual configuration is rarely, if at all, possible, as the
necessary skills are missing in typical installation environments
(such as in family homes).
o There may be a large number of devices. Configuration tasks that
may be acceptable when performed for one device may become
unacceptable with dozens or hundreds of devices.
o Smart object networks may rely on different radio technologies.
Provisioning methods that rely on specific link-layer features may
not work with other radio technologies in a heterogeneous network.
o Network configurations evolve over the lifetime of the devices, as
additional devices are introduced or addresses change. Various
central nodes may also receive more frequent updates than
individual devices such as sensors embedded in building materials.
In light of the above challenges, resource-constrained devices are
often shipped with a single static identity. In many cases, it is a
single raw public key. These long-term static identities makes it
easy to track the devices (and their owners) when they move. The
static identities may also allow an attacker to track these devices
across ownership changes.
Finally, layering and communication models present difficulties for
straightforward use of the most obvious security mechanisms. Smart
object networks typically pass information through multiple
participating nodes [I-D.arkko-core-sleepy-sensors] and end-to-end
security for IP or transport layers may not fit such communication
models very well. The primary reasons for needing middleboxes
relates to the need to accommodate for sleeping nodes as well to
enable the implementation of nodes that store or aggregate
information.
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4. Proposed Deployment Model
[I-D.arkko-core-security-arch] recognizes the provisioning model as
the driver of what kind of security architecture is useful. This
section re-introduces this model briefly here in order to facilitate
the discussion of the various design alternatives later.
The basis of the proposed architecture are self-generated secure
identities, similar to Cryptographically Generated Addresses (CGAs)
[RFC3972] or Host Identity Tags (HITs) [RFC7401]. That is, we assume
the following holds:
I = h(P|O)
where I is the secure identity of the device, h is a hash function, P
is the public key from a key pair generated by the device, and O is
optional other information. | here denotes the concatenation
operator.
4.1. Provisioning
As it is difficult to provision security credentials, shared secrets,
and policy information, the provisioning model is based only on the
secure identities. A typical network installation involves physical
placement of a number of devices while noting the identities of these
devices. This list of short identifiers can then be fed to a central
server as a list of authorized devices. Secure communications can
then commence with the devices, at least as far as information from
from the devices to the server is concerned, which is what is needed
for sensor networks.
The above architecture is a perfect fit for sensor networks where
information flows from large number of devices to small number of
servers. But it is not sufficient alone for other types of
applications. For instance, in actuator applications a large number
of devices need to take commands from somewhere else. In such
applications it is necessary to secure that the commands come from an
authorized source.
This can be supported, with some additional provisioning effort and
optional pairing protocols. The basic provisioning approach is as
described earlier, but in addition there must be something that
informs the devices of the identity of the trusted server(s). There
are multiple ways to provide this information. One simple approach
is to feed the identities of the trusted server(s) to devices at
installation time. This requires either a separate user interface,
local connection (such as USB), or using the network interface of the
device for configuration. In any case, as with sensor networks the
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amount of configuration information is minimized: just one short
identity value needs to be fed in (not both an identity and
certificate or shared secrets that must be kept confidential). An
even simpler provisioning approach is that the devices in the device
group trust each other. Then no configuration is needed at
installation time.
Once both the parties interested in communicating know the expected
cryptographic identity of the other off-line, secure communications
can commence. Alternatively, various pairing schemes can be
employed. Note that these schemes can benefit from the already
secure identifiers on the device side. For instance, the server can
send a pairing message to each device after their initial power-on
and before they have been paired with anyone, encrypted with the
public key of the device. As with all pairing schemes that do not
employ a shared secret or the secure identity of both parties, there
are some remaining vulnerabilities that may or may not be acceptable
for the application in question. For example, many leap-of-faith or
trust-on-first-use based pairing methods assume that the attacker is
not present during the initial setup. Therefore, they are vulnerable
to eavesdropping or man-in-the-middle (MitM) attacks.
In any case, the secure identities help again in ensuring that the
operations are as simple as possible. Only identities need to be
communicated to the devices, not certificates, not shared secrets or
e.g. IPsec policy rules.
Where necessary, the information collected at installation time may
also include other parameters relevant to the application, such as
the location or purpose of the devices. This would enable the server
to know, for instance, that a particular device is the temperature
sensor for the kitchen.
Collecting the identity information at installation time can be
arranged in a number of ways. One simple but not completely secure
method where the last few digits of the identity are printed on a
tiny device just a few millimeters across. Alternatively, the
packaging for the device may include the full identity (typically 32
hex digits), retrieved from the device at manufacturing time. This
identity can be read, for instance, by a bar code reader carried by
the installation personnel. (Note that the identities are not
secret, the security of the system is not dependent on the identity
information leaking to others. The real owner of an identity can
always prove its ownership with the private key which never leaves
the device.) Finally, the device may use its wired network interface
or proximity-based communications, such as Near-Field Communications
(NFC) or Radio-Frequency Identity tags (RFIDs). Such interfaces
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allow secure communication of the device identity to an information
gathering device at installation time.
No matter what the method of information collection is, this
provisioning model minimizes the effort required to set up the
security. Each device generates its own identity in a random, secure
key generation process. The identities are self-securing in the
sense that if you know the identity of the peer you want to
communicate with, messages from the peer can be signed by the peer's
private key and it is trivial to verify that the message came from
the expected peer. There is no need to configure an identity and
certificate of that identity separately. There is no need to
configure a group secret or a shared secret. There is no need to
configure a trust anchor. In addition, the identities are typically
collected anyway for application purposes (such as identifying which
sensor is in which room). Under most circumstances there is actually
no additional configuration effort from provisioning security.
As discussed in the previous section, long-term static identities
negatively affect the privacy of the devices and their owners.
Therefore, it is beneficial for devices to generate new identities at
appropriate times during their lifecycle. For example, after a
factory reset or an ownership handover. Thus, in our proposed
deployment model, the devices would generate a new asymmetric key
pair and use the new public-key P' to generate the new identity I'.
It is also desirable that these identities are only used during the
provisioning stage. Temporary identities (such as dynamic IPv6
addresses) can be used for network communication protocols once the
device is operational.
Groups of devices can be managed through single identifiers as well.
In these deployment cases it is also possible to configure the
identity of an entire group of devices, rather than registering the
individual devices. For instance, many installations employ a kit of
devices bought from the same manufacturer in one package. It is easy
to provide an identity for such a set of devices as follows:
Idev = h(Pdev|Potherdev1|Potherdev2|...|Potherdevn)
Igrp = h(Pdev1|Pdev2|...|Pdevm)
where Idev is the identity of an individual device, Pdev is the
public key of that device, and Potherdevi are the public keys of
other devices in the group, n is all the devices in the group except
the device with Pdev as its public key, and m is the total number of
devices in the group. Now, we can define the secure identity of the
group (Igrp) as a hash of all the public keys of the devices in the
group (Pdevi).
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The installation personnel can scan the identity of the group from
the box that the kit came in, and this identity can be stored in a
server that is expected to receive information from the nodes. Later
when the individual devices contact this server, they will be able to
show that they are part of the group, as they can reveal their own
public key and the public keys of the other devices. Devices that do
not belong to the kit can not claim to be in the group, because the
group identity would change if any new keys were added to the
identity of the group (Igrp).
4.2. Protocol Architecture
As noted above, the starting point of the architecture is that nodes
self-generate secure identities which are then communicated out-of-
band to the peers that need to know what devices to trust. To
support this model in a protocol architecture, we also need to use
these secure identities to implement secure messaging between the
peers, explain how the system can respond to different types of
attacks such as replay attempts, and decide at what protocol layer
and endpoints the architecture should use.
The deployment itself is suitable for a variety of design choices
regarding layering and protocol mechanisms.
[I-D.arkko-core-security-arch] was mostly focused on employing end-
to-end data object security as opposed to hop-by-hop security. But
other approaches are possible. For instance, HIP in its
opportunistic mode could be used to implement largely the same
functionality at the IP layer. However, it is our belief that the
right layer for this solution is at the application layer. More
specifically, in the data formats transported in the payload part of
CoAP. This approach provides the following benefits:
o Ability for intermediaries to act as caches to support different
sleep schedules, without the security model being impacted.
o Ability for intermediaries to be built to perform aggregation,
filtering, storage and other actions, again without impacting the
security of the data being transmitted or stored.
o Ability to operate in the presence of traditional middleboxes,
such as a protocol translators or even NATs (not that we recommend
their use in these environments).
However, as we will see later there are also some technical
implications, namely that link, network, and transport layer
solutions are more likely to be able to benefit from sessions where
the cost of expensive operations can be amortized over multiple data
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transmissions. While this is not impossible in data object security
solutions, it is generally not the typical arrangement.
5. Code Availability
For implementing public key cryptography on resource constrained
environments, we chose Arduino Uno board [arduino-uno] as the test
platform. Arduino Uno has an ATmega328 microcontroller, an 8-bit
processor with a clock speed of 16 MHz, 2 kB of RAM, and 32 kB of
flash memory. Our choice of a 8-bit platform may seem surprising
since cheaper and more energy-efficient 32-bit platforms are
available. However, our intention was to evaluate the performance of
public-key cryptography on the most resource-constrained platforms
available. It is reasonable to expect better performance results
from 32-bit microcontrollers.
For selecting potential asymmetric cryptographic libraries, we
surveyed and came up with a set of possible code sources, and
performed an initial analysis of how well they fit the Arduino
environment. Note that the results are preliminary, and could easily
be affected in any direction by implementation bugs, configuration
errors, and other mistakes. It is advisable to verify the numbers
before relying on them for building something. No significant effort
was done to optimize ROM memory usage beyond what the libraries
provided themselves, so those numbers should be taken as upper
limits.
Here is the set of libraries we found:
o AvrCryptolib [avr-cryptolib]: This library provides symmetric key
algorithms such as AES. It provides RSA as an asymmetric key
algorithm. Parts of the library were written in AVR-8 bit
assembly language to reduce the size and optimize the performance.
o Relic-Toolkit [relic-toolkit]: This library is written entirely in
C and provides a highly flexible and customizable implementation
of a large variety of cryptographic algorithms. This not only
includes RSA and ECC, but also pairing based asymmetric
cryptography, Boneh-Lynn-Schacham, Boneh-Boyen short signatures.
The library has also added support for curve25519 (for elliptic
curve Diffie-Hellman key exchange) [RFC7748] and edwards25519 (for
elliptic curve digital signatures) [RFC8032]. The toolkit
provides an option to build only the desired components for the
required platform.
o TinyECC [tinyecc]: TinyECC was designed for using elliptic curve
based public key cryptography on sensor networks. It is written
in the nesC programming language [nesC] and as such is designed
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for specific use on TinyOS. However, the library can be ported to
standard C either with tool-chains or manually rewriting parts of
the code. It also has one of the smallest memory footprints among
the set of elliptic curve libraries surveyed so far.
o Wiselib [wiselib]: Wiselib is a generic library written for sensor
networks containing a wide variety of algorithms. While the
stable version contains algorithms for routing only, the test
version includes many more algorithms including algorithms for
cryptography, localization, topology management and many more.
The library was designed with the idea of making it easy to
interface the library with operating systems like iSense and
Contiki. However, since the library is written entirely in C++
with a template based model similar to Boost/CGAL, it can be used
on any platform directly without using any of the operating system
interfaces provided. This approach was taken to test the code on
Arduino Uno.
o MatrixSSL [matrix-ssl]: This library provides a low footprint
implementation of several cryptographic algorithms including RSA
and ECC (with a commercial license). The library in the original
form takes about 50 kB of ROM and is intended for 32-bit
platforms.
This is by no ways an exhaustive list and there exist other
cryptographic libraries targeting resource-constrained devices.
There are also a number of operating systems that are specifically
targeted for resource-constrained devices. These operating systems
may included libraries and code for security. Hahm et al.[hahmos]
conduct a survey of such operating systems. The ARM mbed OS [mbed]
is one such operating system that provides various cryptographic
primitives that are necessary for SSL/TLS protocol implementation as
well as X509 certificate handling. The library provides an API for
developer with a minimal code footprint. It is intended for various
ARM platforms such as ARM Cortex M0, ARM Cortex M0+ and ARM Cortex
M3.
6. Implementation Experiences
While evaluating the implementation experiences, we were particularly
interested in the signature generation operation. This was because
our example application discussed in Section 7 required only the
signature generation operation on the resource-constrained platforms.
We have summarized the initial results of RSA private key
exponentiation performance using AvrCryptolib [avr-crypto-lib] in
Table 1. All results are from a single run since repeating the test
did not change (or had only minimal impact on) the results. The
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execution time for a key size of 2048 bits was inordinately long and
would be a deterrent in real-world deployments.
+--------------+------------------------+---------------------------+
| Key length | Execution time (ms); | Memory footprint (bytes); |
| (bits) | key in RAM | key in RAM |
+--------------+------------------------+---------------------------+
| 2048 | 1587567 | 1280 |
+--------------+------------------------+---------------------------+
RSA private key operation performance
Table 1
The code size was about 3.6 kB with potential for further reduction.
It is also worth noting that the implementation performs basic
exponentiation and multiplication operations without using any
mathematical optimizations such as Montgomery multiplication,
optimized squaring, etc. as described in [rsa-high-speed]. With more
RAM, we believe that 2048-bit operations can be performed in much
less time as has been shown in [rsa-8bit].
In Table 2 we present the results obtained by manually porting
TinyECC into C99 standard and running the Elliptic Curve Digital
Signature Algorithm (ECDSA) on the Arduino Uno board. TinyECC
supports a variety of SEC 2 recommended Elliptic Curve domain
parameters [sec2ecc]. The execution time and memory footprint are
shown next to each of the curve parameters. These results were
obtained by turning on all the optimizations and using assembly code
where available.
The results from the performance evaluation of ECDSA in the following
tables also contains a column stating the approximate comparable RSA
key length as documented in [sec2ecc]. It is clearly observable that
for similar security levels, Elliptic Curve public key cryptography
outperforms RSA.
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+-------------+---------------+-----------------+-------------------+
| Curve | Execution | Memory | Comparable RSA |
| parameters | time (ms) | Footprint | key length |
| | | (bytes) | |
+-------------+---------------+-----------------+-------------------+
| secp160k1 | 2228 | 892 | 1024 |
| secp160r1 | 2250 | 892 | 1024 |
| secp160r2 | 2467 | 892 | 1024 |
| secp192k1 | 3425 | 1008 | 1536 |
| secp192r1 | 3578 | 1008 | 1536 |
+-------------+---------------+-----------------+-------------------+
Performance of ECDSA sign operation with TinyECC
Table 2
We also performed experiments by removing the assembly optimization
and using a C only form of the library. This gives us an idea of the
performance that can be achieved with TinyECC on any platform
regardless of what kind of OS and assembly instruction set available.
The memory footprint remains the same with or without assembly code.
The tables contain the maximum RAM that is used when all the possible
optimizations are on. If however, the amount of RAM available is
smaller in size, some of the optimizations can be turned off to
reduce the memory consumption accordingly.
+-------------+---------------+-----------------+-------------------+
| Curve | Execution | Memory | Comparable RSA |
| parameters | time (ms) | Footprint | key length |
| | | (bytes) | |
+-------------+---------------+-----------------+-------------------+
| secp160k1 | 3795 | 892 | 1024 |
| secp160r1 | 3841 | 892 | 1024 |
| secp160r2 | 4118 | 892 | 1024 |
| secp192k1 | 6091 | 1008 | 1536 |
| secp192r1 | 6217 | 1008 | 1536 |
+-------------+---------------+-----------------+-------------------+
Performance of ECDSA sign operation with TinyECC (No assembly
optimizations)
Table 3
Table 4 documents the performance of Wiselib. Since there were no
optimizations that could be turned on or off, we have only one set of
results. By default Wiselib only supports some of the standard SEC 2
Elliptic curves, but it is easy to change the domain parameters and
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obtain results for all the 128, 160 and 192-bit SEC 2 Elliptic
curves. The ROM size for all the experiments was less than 16 kB.
+-------------+---------------+-----------------+-------------------+
| Curve | Execution | Memory | Comparable RSA |
| parameters | time (ms) | Footprint | key length |
| | | (bytes) | |
+-------------+---------------+-----------------+-------------------+
| secp160k1 | 10957 | 842 | 1024 |
| secp160r1 | 10972 | 842 | 1024 |
| secp160r2 | 10971 | 842 | 1024 |
| secp192k1 | 18814 | 952 | 1536 |
| secp192r1 | 18825 | 952 | 1536 |
+-------------+---------------+-----------------+-------------------+
Performance ECDSA sign operation with Wiselib
Table 4
For testing the relic-toolkit we used a different board because it
required more RAM/ROM and we were unable to perform experiments with
it on Arduino Uno. Arduino Mega has the same 8-bit architecture like
the Arduino Uno but has a much larger RAM/ROM. We used Arduino Mega
for experimenting with the relic-toolkit. Again, it is important to
mention that we used Arduino as it is a convenient prototyping
platform. Our intention was to demonstrate the feasibility of the
entire architecture with public key cryptography on an 8-bit
microcontroller. However it is important to state that 32-bit
microcontrollers are much more easily available, at lower costs and
are more power efficient. Therefore, real deployments are better off
using 32-bit microcontrollers that allow developers to include the
necessary cryptographic libraries. There is no good reason to choose
platforms that do not provide sufficient computing power to run the
necessary cryptographic operations.
The relic-toolkit supports Koblitz curves over prime as well as
binary fields. We have experimented with Koblitz curves over binary
fields only. We do not run our experiments with all the curves
available in the library since the aim of this work is not prove
which curves perform the fastest, and rather show that asymmetric
cryptography is possible on resource-constrained devices.
The results from relic-toolkit are documented in two separate tables
shown in Table 5 and Table 6. The first set of results were
performed with the library configured for high speed performance with
no consideration given to the amount of memory used. For the second
set, the library was configured for low memory usage irrespective of
the execution time required by different curves. By turning on/off
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optimizations included in the library, a trade-off between memory and
execution time between these values can be achieved.
+-----------------+--------------+----------------+-----------------+
| Curve | Execution | Memory | Comparable RSA |
| parameters | time (ms) | Footprint | key length |
| | | (bytes) | |
+-----------------+--------------+----------------+-----------------+
| sect163k1 | 261 | 2804 | 1024 |
| (assembly math) | | | |
| sect163k1 | 932 | 2750 | 1024 |
| sect163r2 | 2243 | 2444 | 1024 |
| sect233k1 | 1736 | 3675 | 2048 |
| sect233r1 | 4471 | 3261 | 2048 |
+-----------------+--------------+----------------+-----------------+
Performance of ECDSA sign operation with relic-toolkit (Fast)
Table 5
+-----------------+--------------+----------------+-----------------+
| Curve | Execution | Memory | Comparable RSA |
| parameters | time (ms) | Footprint | key length |
| | | (bytes) | |
+-----------------+--------------+----------------+-----------------+
| sect163k1 | 592 | 2087 | 1024 |
| (assembly math) | | | |
| sect163k1 | 2950 | 2215 | 1024 |
| sect163r2 | 3213 | 2071 | 1024 |
| sect233k1 | 6450 | 2935 | 2048 |
| sect233r1 | 6100 | 2737 | 2048 |
+-----------------+--------------+----------------+-----------------+
Performance of ECDSA sign operation with relic-toolkit (Low Memory)
Table 6
It is important to note the following points about the elliptic curve
measurements:
o Some boards (e.g. Arduino Uno) do not provide a hardware random
number generator. On such boards, obtaining cryptographic-quality
randomness is a challenge. Real-world deployments must rely on a
hardware random number generator for cryptographic operations such
as generating a public-private key pair. The Nordic nRF52832
board [nordic] for example provides a hardware random number
generator. A detailed discussion on requirements and best
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practices for cryptographic-quality randomness is documented in
[RFC4086]
o For measuring the memory footprint of all the ECC libraries, we
used the Avrora simulator [avrora]. Only stack memory was used to
easily track the RAM consumption.
Tschofenig and Pegourie-Gonnard [armecdsa] have also evaluated the
performance of Elliptic Curve Cryptography (ECC) on ARM Coretex
platform. The results for ECDSA sign operation shown in Table 7 are
performed on a Freescale FRDM-KL25Z board [freescale] that has a ARM
Cortex-M0+ 48MHz microcontroller with 128kB of flash memory and 16kB
of RAM. The sliding window technique for efficient exponentiation
was used with a window size of 2. All other optimizations were
disabled for these measurements.
+------------------+---------------------+--------------------------+
| Curve parameters | Execution time (ms) | Comparable RSA key |
| | | length |
+------------------+---------------------+--------------------------+
| secp192r1 | 2165 | 1536 |
| secp224r1 | 3014 | 2048 |
| secp256r1 | 3649 | 2048 |
+------------------+---------------------+--------------------------+
Performance of ECDSA sign operation with ARM mbed TLS stack on
Freescale FRDM-KL25Z
Table 7
Tschofenig and Pegourie-Gonnard [armecdsa] also measured the
performance of curves on a ST Nucleo F091 (STM32F091RCT6) board
[stnucleo] that has a ARM Cortex-M0 48MHz microcontroller with 256 kB
of flash memory and 32kB of RAM. The execution time for ECDSA sign
operation with different curves is shown in Table 8. The sliding
window technique for efficient exponentiation was used with a window
size of 7. Fixed point optimization and NIST curve specific
optimizations were used for these measurements.
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+------------------+---------------------+--------------------------+
| Curve parameters | Execution time (ms) | Comparable RSA key |
| | | length |
+------------------+---------------------+--------------------------+
| secp192k1 | 291 | 1536 |
| secp192r1 | 225 | 1536 |
| secp224k1 | 375 | 2048 |
| secp224r1 | 307 | 2048 |
| secp256k1 | 486 | 2048 |
| secp256r1 | 459 | 2048 |
| secp384r1 | 811 | 7680 |
| secp521r1 | 1602 | 15360 |
+------------------+---------------------+--------------------------+
ECDSA signature performance with ARM mbed TLS stack on ST Nucleo F091
(STM32F091RCT6)
Table 8
Finally, Tschofenig and Pegourie-Gonnard [armecdsa] also measured the
RAM consumption by calculating the heap consumed for the
cryptographic operations using a custom memory allocation handler.
They did not measure the minimal stack memory consumption. Depending
on the curve and the different optimizations enable or disabled, the
memory consumption for the ECDSA sign operation varied from 1500
bytes to 15000 bytes.
At the time of performing these measurements and study, it was
unclear which exact elliptic curve(s) would be selected by the IETF
community for use with resource-constrained devices. However now,
[RFC7748] defines two elliptic curves over prime fields (Curve25519
and Curve448) that offer a high level of practical security for
Diffie-Hellman key exchange. Correspondingly, there is ongoing work
to specify elliptic curve signature schemes with Edwards-curve
Digital Signature Algorithm (EdDSA). [RFC8032] specifies the
recommended parameters for the edwards25519 and edwards448 curves.
From these, curve25519 (for elliptic curve Diffie-Hellman key
exchange) and edwards25519 (for elliptic curve digital signatures)
are especially suitable for resource-constrained devices.
We found that the NaCl [nacl] and MicoNaCl [micronacl] libraries
provide highly efficient implementations of Diffie-Hellman key
exchange with curve25519. The results have shown that these
libraries with curve25519 outperform other elliptic curves that
provide similar levels of security. Hutter and Schwabe [naclavr]
also show that signing of data using the curve Ed25519 from the NaCl
library needs only 23216241 cycles on the same microcontroller that
we used for our evaluations (Arduino Mega ATmega2560). This
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corresponds to about 1451 milliseconds of execution time. When
compared to the results for other curves and libraries that offer
similar level of security (such as NIST B233, NIST K233), this
implementation far outperforms all others. As such, it is recommend
that the IETF community uses these curves for protocol specification
and implementations.
A summary library flash memory use is shown in Table 9.
+------------------------+------------------------------------+
| Library | Flash memory Footprint (Kilobytes) |
+------------------------+------------------------------------+
| AvrCryptolib | 3.6 |
| Wiselib | 16 |
| TinyECC | 18 |
| Relic-toolkit | 29 |
| NaCl Ed25519 [naclavr] | 17-29 |
+------------------------+------------------------------------+
Summary of library flash memory consumption
Table 9
All the measurements here are only provided as an example to show
that asymmetric-key cryptography (particularly, digital signatures)
is possible on resource-constrained devices. These numbers by no way
are the final source for measurements and some curves presented here
may not be acceptable for real in-the-wild deployments anymore. For
example, Mosdorf et al. [mosdorf] and Liu et al. [tinyecc] also
document performance of ECDSA on similar resource-constrained
devices.
7. Example Application
We developed an example application on the Arduino platform to use
public key crypto mechanisms, data object security, and an easy
provisioning model. Our application was originally developed to test
different approaches to supporting communications to "always off"
sensor nodes. These battery-operated or energy scavenging nodes do
not have enough power to stay on at all times. They wake up
periodically and transmit their readings.
Such sensor nodes can be supported in various ways.
[I-D.arkko-core-sleepy-sensors] was an early multicast-based
approach. In the current application we have switched to using
resource directories [I-D.ietf-core-resource-directory] and publish-
subscribe brokers [I-D.ietf-core-coap-pubsub] instead.
Architecturally, the idea is that sensors can delegate a part of
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their role to a node in the network. Such a network node could be
either a local resource or something in the Internet. In the case of
CoAP publish-subscribe brokers, the network node agrees to hold the
web resources on behalf of the sensor, while the sensor is asleep.
The only role that the sensor has is to register itself at the
publish-subscribe broker, and periodically update the readings. All
queries from the rest of the world go to the publish-subscribe
broker.
We constructed a system with four entities:
Sensor
This is an Arduino-based device that runs a CoAP publish-subscribe
broker client and Relic-toolkit. Relic takes 29 Kbytes of flash
memory, and the simple CoAP client roughly 3 kilobytes.
Publish-Subscribe Broker
This is a publish-subscribe broker that holds resources on the
sensor's behalf. The sensor registers itself to this node.
Resource Directory
While physically in the same node in our implementation, a
resource directory is a logical function that allows sensors and
publish-subscribe brokers to register resources in the directory.
These resources can be queried by applications.
Application
This is a simple application that runs on a general purpose
computer and can retrieve both registrations from the resource
directory and most recent sensor readings from the publish-
subscribe broker.
The security of this system relies on an SSH-like approach. In Step
1, upon first boot, sensors generate keys and register themselves in
the publish-subscribe broker. Their public key is submitted along
with the registration as an attribute in the CORE Link Format data
[RFC6690].
In Step 2, when the sensor makes a measurement, it sends an update to
the publish-subscribe broker and signs the message contents with a
JOSE signature on the used JSON/SENML payload [RFC7515]
[I-D.ietf-core-senml]. The sensor can also alternatively use CBOR
Object Signing and Encryption (COSE) [RFC8152] for signing the sensor
measurement.
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In Step 3, any other device in the network -- including the publish-
subscribe broker, resource directory and the application -- can check
that the public key from the registration corresponds to the private
key used to make the signature in the data update.
Note that checks can be done at any time and there is no need for the
sensor and the checking node to be awake at the same time. In our
implementation, the checking is done in the application node. This
demonstrates how it is possible to implement end-to-end security even
with the presence of assisting middleboxes.
To verify the feasibility of our architecture we developed a proof-
of-concept prototype. In our prototype, the sensor was implemented
using the Arduino Ethernet shield over an Arduino Mega board. Our
implementation uses the standard C99 programming language on the
Arduino Mega board. In this prototype, the publish-subscribe broker
and the Resource Directory (RD) reside on the same physical host. A
64-bit x86 linux machine serves as the broker and the RD, while a
similar but physically distinct 64-bit x86 linux machine serves as
the client that requests data from the sensor. We chose the Relic
library version 0.3.1 for our sample prototype as it can be easily
compiled for different bit-length processors. Therefore, we were
able to use it on the 8-bit processor of the Arduino Mega, as well as
on the 64-bit processor of the x86 client. We used ECDSA to sign and
verify data updates with the standard NIST-K163 curve parameters.
While compiling Relic for our prototype, we used the fast
configuration without any assembly optimizations.
The gateway implements the CoAP base specification in the Java
programming language and extends it to add support for publish-
subscribe broker and Resource Directory REST interfaces. We also
developed a minimalistic CoAP C-library for the Arduino sensor and
for the client requesting data updates for a resource. The library
has small RAM requirements and uses stack-based allocation only. It
is interoperable with the Java implementation of CoAP running on the
gateway. The location of the resource directory was configured into
the smart object sensor by hardcoding the IP address. A real
implementation based on this prototype would instead use the domain
name system for obtaining the location of the resource directory.
Our intention was to demonstrate that it is possible to implement the
entire architecture with public-key cryptography on an 8-bit
microcontroller. The stated values can be improved further by a
considerable amount. For example, the flash memory and RAM
consumption is relatively high because some of the Arduino libraries
were used out-of-the-box and there are several functions which can be
removed. Similarly we used the fast version of the Relic library in
the prototype instead of the low memory version. However, it is
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important to note that this was only a research prototype to verify
the feasibility of this architecture and as stated elsewhere, most
modern development boards have a 32-bit microcontroller since they
are more economical and have better energy efficiency.
8. Design Trade-Offs
This section attempts to make some early conclusions regarding trade-
offs in the design space, based on deployment considerations for
various mechanisms and the relative ease or difficulty of
implementing them. In particular, this analysis looks at layering,
freshness and the choice of symmetric vs. asymmetric cryptography.
8.1. Feasibility
The first question is whether using cryptographic security and
asymmetric cryptography in particular is feasible at all on resource-
constrained devices. The numbers above give a mixed message.
Clearly, an implementation of a significant cryptographic operation
such as public key signing can be done in surprisingly small amount
of code space. It could even be argued that our chosen prototype
platform was unnecessarily restrictive in the amount of code space it
allows: we chose this platform on purpose to demonstrate something
that is as resource-constrained and difficult as possible.
A recent trend in microcontrollers is the introduction of 32-bit CPUs
that are becoming cheaper and more easily available than 8-bit CPUs,
in addition to being more easily programmable. The flash memory size
is probably easier to grow than other parameters in microcontrollers.
Flash memory size is not expected to be the most significant limiting
factor. Before picking a platform, developers should also plan for
firmware updates. This would essentially mean that the platform
should at least have a flash memory size of the total code size * 2,
plus some space for buffer.
The situation is less clear with regards to the amount of CPU power
needed to run the algorithms. The demonstrated speeds are sufficient
for many applications. For instance, a sensor that wakes up every
now and then can likely spend a fraction of a second, or even spend
multiple seconds in some cases, for the computation of a signature
for the message that it is about to send. Most applications that use
protocols such as DTLS that use public key cryptography only at the
beginning of the session would also be fine with any of these
execution times.
Yet, with reasonably long key sizes the execution times are in the
seconds, dozens of seconds, or even longer. For some applications
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this is too long. Nevertheless, these algorithms can successfully be
employed in resource-constrained devices for the following reasons:
o With the right selection of algorithms and libraries, the
execution times can actually be very small (less than 500 ms).
o As discussed in [wiman], in general the power requirements
necessary to turn the radio on/off and sending or receiving
messages are far bigger than those needed to execute cryptographic
operations. While there are newer radios that significantly lower
the energy consumption of sending and receiving messages, there is
no good reason to choose platforms that do not provide sufficient
computing power to run the necessary cryptographic operations.
o Commercial libraries and the use of full potential for various
optimizations will provide a better result than what we arrived at
in this memo.
o Using public-key cryptography only at the beginning of a session
will reduce the per-packet processing times significantly.
While we did not do an exhaustive performance evaluation of
asymmetric key pair generation on resource-constrained devices, we
did note that it is possible for such devices to generate a new key
pair. Given that this operation would only occur in rare
circumstances (such as a factory reset or ownership change) and its
potential privacy benefits, developers should provide mechanisms for
generating new identities. It is however extremely important to note
that the security of this operation relies on access to
cryptographic-quality randomness.
8.2. Freshness
In our architecture, if implemented as described thus far, messages
along with their signatures sent from the sensors to the publish-
subscribe broker can be recorded and replayed by an eavesdropper.
The publish-subscribe broker has no mechanism to distinguish
previously received packets from those that are retransmitted by the
sender or replayed by an eavesdropper. Therefore, it is essential
for the smart objects to ensure that data updates include a freshness
indicator. However, ensuring freshness on constrained devices can be
non-trivial because of several reasons which include:
o Communication is mostly unidirectional to save energy.
o Internal clocks might not be accurate and may be reset several
times during the operational phase of the smart object.
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o Network time synchronization protocols such as Network Time
Protocol (NTP) [RFC5905] are resource intensive and therefore may
be undesirable in many smart object networks.
There are several different methods that can be used in our
architecture for replay protection. The selection of the appropriate
choice depends on the actual deployment scenario.
Including sequence numbers in signed messages can provide an
effective method of replay protection. The publish-subscribe broker
should verify the sequence number of each incoming message and accept
it only if it is greater than the highest previously seen sequence
number. The publish-subscribe broker drops any packet with a
sequence number that has already been received or if the received
sequence number is greater than the highest previously seen sequence
number by an amount larger than the preset threshold.
Sequence numbers can wrap around at their maximum value and,
therefore, it is essential to ensure that sequence numbers are
sufficiently long. However, including long sequence numbers in
packets can increase the network traffic originating from the sensor
and can thus decrease its energy efficiency. To overcome the problem
of long sequence numbers, we can use a scheme similar to that of
Huang [huang], where the sender and receiver maintain and sign long
sequence numbers of equal bit-lengths but they transmit only the
least significant bits.
It is important for the smart object to write the sequence number
into the permanent flash memory after each increment and before it is
included in the message to be transmitted. This ensures that the
sensor can obtain the last sequence number it had intended to send in
case of a reset or a power failure. However, the sensor and the
publish-subscribe broker can still end up in a discordant state where
the sequence number received by the publish-subscribe broker exceeds
the expected sequence number by an amount greater than the preset
threshold. This may happen because of a prolonged network outage or
if the publish-subscribe broker experiences a power failure for some
reason. Therefore it is essential for sensors that normally send
Non-Confirmable data updates to send some Confirmable updates and re-
synchronize with the publish-subscribe broker if a reset message is
received. The sensors re-synchronize by sending a new registration
message with the current sequence number.
Although sequence numbers protect the system from replay attacks, a
publish-subscribe broker has no mechanism to determine the time at
which updates were created by the sensor. Moreover, if sequence
numbers are the only freshness indicator used, a malicious
eavesdropper can induce inordinate delays to the communication of
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signed updates by buffering messages. It may be important in certain
smart object networks for sensors to send data updates which include
timestamps to allow the publish-subscribe broker to determine the
time when the update was created. For example, when the publish-
subscribe broker is collecting temperature data, it may be necessary
to know when exactly the temperature measurement was made by the
sensor. A simple solution to this problem is for the publish-
subscribe broker to assume that the data object was created when it
receives the update. In a relatively reliable network with low RTT,
it can be acceptable to make such an assumption. However most
networks are susceptible to packet loss and hostile attacks making
this assumption unsustainable.
Depending on the hardware used by the smart objects, they may have
access to accurate hardware clocks which can be used to include
timestamps in the signed updates. These timestamps are included in
addition to sequence numbers. The clock time in the smart objects
can be set by the manufacturer or the current time can be
communicated by the publish-subscribe broker during the registration
phase. However, these approaches require the smart objects to either
rely on the long-term accuracy of the clock set by the manufacturer
or to trust the publish-subscribe broker thereby increasing the
potential vulnerability of the system. The smart objects could also
obtain the current time from NTP, but this may consume additional
energy and give rise to security issues discussed in [RFC5905]. The
smart objects could also have access to a mobile network or the
Global Positioning System (GPS), and they can be used obtain the
current time. Finally, if the sensors need to co-ordinate their
sleep cycles, or if the publish-subscribe broker computes an average
or mean of updates collected from multiple smart objects, it is
important for the network nodes to synchronize the time among them.
This can be done by using existing synchronization schemes.
8.3. Layering
It would be useful to select just one layer where security is
provided at. Otherwise a simple device needs to implement multiple
security mechanisms. While some code can probably be shared across
such implementations (like algorithms), it is likely that most of the
code involving the actual protocol machinery cannot. Looking at the
different layers, here are the choices and their implications:
link layer
This is probably the most common solution today. The biggest
benefits of this choice of layer are that security services are
commonly available (WLAN secrets, cellular SIM cards, etc.) and
that their application protects the entire communications.
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The main drawback is that there is no security beyond the first
hop. This can be problematic, e.g., in many devices that
communicate to a server in the Internet. A Withings scale
[Withings], for instance, can support WLAN security but without
some level of end-to-end security, it would be difficult to
prevent fraudulent data submissions to the servers.
Another drawback is that some commonly implemented link layer
security designs use group secrets. This allows any device within
the local network (e.g., an infected laptop) to attack the
communications.
network layer
There are a number of solutions in this space, and many new ones
and variations thereof being proposed: IPsec, PANA, and so on. In
general, these solutions have similar characteristics to those in
the transport layer: they work across forwarding hops but only as
far as to the next middlebox or application entity. There is
plenty of existing solutions and designs.
Experience has shown that it is difficult to control IP layer
entities from an application process. While this is theoretically
easy, in practice the necessary APIs do not exist. For instance,
most IPsec software has been built for the VPN use case, and is
difficult or impossible to tweak to be used on a per-application
basis. As a result, the authors are not particularly enthusiastic
about recommending these solutions.
transport and application layer
This is another popular solution along with link layer designs.
TLS with HTTP (HTTPS) and DTLS with CoAP are examples of solutions
in this space, and have been proven to work well. These solutions
are typically easy to take into use in an application, without
assuming anything from the underlying OS, and they are easy to
control as needed by the applications. The main drawback is that
generally speaking, these solutions only run as far as the next
application level entity. And even for this case, HTTPS can be
made to work through proxies, so this limit is not unsolvable.
Another drawback is that attacks on link layer, network layer and
in some cases, transport layer, can not be protected against.
However, if the upper layers have been protected, such attacks can
at most result in a denial-of-service. Since denial-of-service
can often be caused anyway, it is not clear if this is a real
drawback.
data object layer
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This solution does not protect any of the protocol layers, but
protects individual data elements being sent. It works
particularly well when there are multiple application layer
entities on the path of the data. Smart object networks are
likely to employ such entities for storage, filtering, aggregation
and other reasons, and as such, an end-to-end solution is the only
one that can protect the actual data.
The downside is that the lower layers are not protected. But
again, as long as the data is protected and checked upon every
time it passes through an application level entity, it is not
clear that there are attacks beyond denial-of-service.
The main question mark is whether this type of a solution provides
sufficient advantages over the more commonly implemented transport
and application layer solutions.
8.4. Symmetric vs. Asymmetric Crypto
The second trade-off that is worth discussing is the use of plain
asymmetric cryptographic mechanisms, plain symmetric cryptographic
mechanisms, or some mixture thereof.
Contrary to popular cryptographic community beliefs, a symmetric
cryptographic solution can be deployed in large scale. In fact, one
of the largest deployment of cryptographic security, the cellular
network authentication system, uses SIM cards that are based on
symmetric secrets. In contrast, public key systems have yet to show
ability to scale to hundreds of millions of devices, let alone
billions. But the authors do not believe scaling is an important
differentiator when comparing the solutions.
As can be seen from the Section 6, the time needed to calculate some
of the asymmetric cryptographic operations with reasonable key
lengths can be significant. There are two contrary observations that
can be made from this. First, recent wisdom indicates that computing
power on resource-constrained devices is far cheaper than
transmission power [wiman], and keeps on becoming more efficient very
quickly. From this we can conclude that the sufficient CPU is or at
least will be easily available.
But the other observation is that when there are very costly
asymmetric operations, doing a key exchange followed by the use of
generated symmetric keys would make sense. This model works very
well for DTLS and other transport layer solutions, but works less
well for data object security, particularly when the number of
communicating entities is not exactly two.
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9. Summary
This document makes several security recommendations based on our
implementation experience. We summarize some of the important ones
here:
o Developers and product designers should choose the hardware after
determining the security requirements for their application
scenario.
o Elliptic Curve Cryptography (ECC) outperforms RSA based operations
and therefore it is recommended for resource-constrained devices.
o Cryptographic-quality randomness is needed for many security
protocols. Developers and vendors should ensure that the
sufficient randomness is available for security critical tasks.
o 32-bit microcontrollers are much more easily available, at lower
costs and are more power efficient. Therefore, real-world
deployments are better off using 32-bit microcontrollers.
o Developers should provide mechanisms for devices to generate new
identities at appropriate times during their lifecycle. For
example, after a factory reset or an ownership handover.
o Planning for firmware updates is important. The hardware platform
chosen should at least have a flash memory size of the total code
size * 2, plus some space for buffer.
10. Security Considerations
This entire memo deals with security issues.
11. IANA Considerations
There are no IANA impacts in this memo.
12. Informative references
[arduino-uno]
Arduino, "Arduino Uno", September 2015,
<http://arduino.cc/en/Main/arduinoBoardUno>.
[armecdsa]
Tschofenig, H. and M. Pegourie-Gonnard, "Performance
Investigations", March 2015,
<https://www.ietf.org/proceedings/92/slides/
slides-92-lwig-3.pdf>.
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[avr-crypto-lib]
AVR-CRYPTO-LIB, "AVR-CRYPTO-LIB", September 2015,
<http://www.das-labor.org/wiki/AVR-Crypto-Lib/en>.
[avr-cryptolib]
Van der Laan, E., "AVR CRYPTOLIB", September 2015,
<http://www.emsign.nl/>.
[avrora] Titzer, Ben., "Avrora", September 2015,
<http://compilers.cs.ucla.edu/avrora/>.
[freescale]
NXP, "Freescale FRDM-KL25Z", June 2017,
<https://developer.mbed.org/platforms/KL25Z/>.
[hahmos] Hahm, O., Baccelli, E., Petersen, H., and N. Tsiftes,
"Operating systems for low-end devices in the internet of
things: a survey", IEEE Internet of Things Journal , 2016.
[huang] Huang, C., "Low-overhead freshness transmission in sensor
networks", 2008.
[I-D.arkko-core-security-arch]
Arkko, J. and A. Keranen, "CoAP Security Architecture",
draft-arkko-core-security-arch-00 (work in progress), July
2011.
[I-D.arkko-core-sleepy-sensors]
Arkko, J., Rissanen, H., Loreto, S., Turanyi, Z., and O.
Novo, "Implementing Tiny COAP Sensors", draft-arkko-core-
sleepy-sensors-01 (work in progress), July 2011.
[I-D.daniel-6lowpan-security-analysis]
Park, S., Kim, K., Haddad, W., Chakrabarti, S., and J.
Laganier, "IPv6 over Low Power WPAN Security Analysis",
draft-daniel-6lowpan-security-analysis-05 (work in
progress), March 2011.
[I-D.ietf-core-coap-pubsub]
Koster, M., Keranen, A., and J. Jimenez, "Publish-
Subscribe Broker for the Constrained Application Protocol
(CoAP)", draft-ietf-core-coap-pubsub-03 (work in
progress), February 2018.
[I-D.ietf-core-resource-directory]
Shelby, Z., Koster, M., Bormann, C., Stok, P., and C.
Amsuess, "CoRE Resource Directory", draft-ietf-core-
resource-directory-12 (work in progress), October 2017.
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[I-D.ietf-core-senml]
Jennings, C., Shelby, Z., Arkko, J., Keranen, A., and C.
Bormann, "Media Types for Sensor Measurement Lists
(SenML)", draft-ietf-core-senml-12 (work in progress),
December 2017.
[I-D.irtf-t2trg-iot-seccons]
Garcia-Morchon, O., Kumar, S., and M. Sethi, "State-of-
the-Art and Challenges for the Internet of Things
Security", draft-irtf-t2trg-iot-seccons-11 (work in
progress), February 2018.
[I-D.moskowitz-hip-dex]
Moskowitz, R. and R. Hummen, "HIP Diet EXchange (DEX)",
draft-moskowitz-hip-dex-05 (work in progress), January
2016.
[I-D.sarikaya-t2trg-sbootstrapping]
Sarikaya, B., Sethi, M., and A. Sangi, "Secure IoT
Bootstrapping: A Survey", draft-sarikaya-t2trg-
sbootstrapping-03 (work in progress), February 2017.
[matrix-ssl]
PeerSec Networks, "Matrix SSL", September 2015,
<http://www.matrixssl.org/>.
[mbed] ARM, "mbed TLS", May 2017,
<https://www.mbed.com/en/technologies/security/mbed-tls/>.
[micronacl]
MicroNaCl, "The Networking and Cryptography library for
microcontrollers", <http://munacl.cryptojedi.org/>.
[mosdorf] Mosdorf, M. and W. Zabolotny, "Implementation of elliptic
curve cryptography for 8 bit and 32 bit embedded systems
time efficiency and power consumption analysis", Pomiary
Automatyka Kontrola , 2010.
[nacl] NaCl, "Networking and Cryptography library",
<http://nacl.cr.yp.to/>.
[naclavr] Hutter, M. and P. Schwabe, "NaCl on 8-Bit AVR
Microcontrollers", International Conference on Cryptology
in Africa , Springer Berlin Heidelberg , 2013.
[nesC] Gay, D., Levis, P., von Behren, R., Welsh, M., Brewer, E.,
and D. Culler, "The nesC language: A holistic approach to
networked embedded systems", ACM SIGPLAN Notices , 2014.
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[nordic] Nordic Semiconductor, "nRF52832 Product Specification",
June 2017, <http://infocenter.nordicsemi.com/pdf/
nRF52832_PS_v1.3.pdf>.
[relic-toolkit]
Aranha, D. and C. Gouv, "Relic Toolkit", September 2015,
<http://code.google.com/p/relic-toolkit/>.
[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>.
[RFC3972] Aura, T., "Cryptographically Generated Addresses (CGA)",
RFC 3972, DOI 10.17487/RFC3972, March 2005,
<https://www.rfc-editor.org/info/rfc3972>.
[RFC4086] Eastlake 3rd, D., Schiller, J., and S. Crocker,
"Randomness Requirements for Security", BCP 106, RFC 4086,
DOI 10.17487/RFC4086, June 2005,
<https://www.rfc-editor.org/info/rfc4086>.
[RFC4303] Kent, S., "IP Encapsulating Security Payload (ESP)",
RFC 4303, DOI 10.17487/RFC4303, December 2005,
<https://www.rfc-editor.org/info/rfc4303>.
[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>.
[RFC5246] Dierks, T. and E. Rescorla, "The Transport Layer Security
(TLS) Protocol Version 1.2", RFC 5246,
DOI 10.17487/RFC5246, August 2008,
<https://www.rfc-editor.org/info/rfc5246>.
[RFC5406] Bellovin, S., "Guidelines for Specifying the Use of IPsec
Version 2", BCP 146, RFC 5406, DOI 10.17487/RFC5406,
February 2009, <https://www.rfc-editor.org/info/rfc5406>.
[RFC5905] Mills, D., Martin, J., Ed., Burbank, J., and W. Kasch,
"Network Time Protocol Version 4: Protocol and Algorithms
Specification", RFC 5905, DOI 10.17487/RFC5905, June 2010,
<https://www.rfc-editor.org/info/rfc5905>.
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[RFC6078] Camarillo, G. and J. Melen, "Host Identity Protocol (HIP)
Immediate Carriage and Conveyance of Upper-Layer Protocol
Signaling (HICCUPS)", RFC 6078, DOI 10.17487/RFC6078,
January 2011, <https://www.rfc-editor.org/info/rfc6078>.
[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>.
[RFC6574] Tschofenig, H. and J. Arkko, "Report from the Smart Object
Workshop", RFC 6574, DOI 10.17487/RFC6574, April 2012,
<https://www.rfc-editor.org/info/rfc6574>.
[RFC6690] Shelby, Z., "Constrained RESTful Environments (CoRE) Link
Format", RFC 6690, DOI 10.17487/RFC6690, August 2012,
<https://www.rfc-editor.org/info/rfc6690>.
[RFC7230] Fielding, R., Ed. and J. Reschke, Ed., "Hypertext Transfer
Protocol (HTTP/1.1): Message Syntax and Routing",
RFC 7230, DOI 10.17487/RFC7230, June 2014,
<https://www.rfc-editor.org/info/rfc7230>.
[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>.
[RFC7748] Langley, A., Hamburg, M., and S. Turner, "Elliptic Curves
for Security", RFC 7748, DOI 10.17487/RFC7748, January
2016, <https://www.rfc-editor.org/info/rfc7748>.
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[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>.
[RFC8032] Josefsson, S. and I. Liusvaara, "Edwards-Curve Digital
Signature Algorithm (EdDSA)", RFC 8032,
DOI 10.17487/RFC8032, January 2017,
<https://www.rfc-editor.org/info/rfc8032>.
[RFC8152] Schaad, J., "CBOR Object Signing and Encryption (COSE)",
RFC 8152, DOI 10.17487/RFC8152, July 2017,
<https://www.rfc-editor.org/info/rfc8152>.
[rsa-8bit]
Gura, N., Patel, A., Wander, A., Eberle, H., and S.
Shantz, "Comparing Elliptic Curve Cryptography and RSA on
8-bit CPUs", 2010.
[rsa-high-speed]
Koc, C., "High-Speed RSA Implementation", November 1994,
<http://cs.ucsb.edu/~koc/docs/r01.pdf>.
[sec2ecc] Certicom Research, "SEC 2: Recommended Elliptic Curve
Domain Parameters", 2000.
[stnucleo]
STMicroelectronics, "NUCLEO-F091RC", June 2017,
<http://www.st.com/en/evaluation-tools/
nucleo-f091rc.html/>.
[tinyecc] North Carolina State University and North Carolina State
University, "TinyECC", 2008,
<http://discovery.csc.ncsu.edu/software/TinyECC/>.
[wiman] Margi, C., Oliveira, B., Sousa, G., Simplicio, M., Paulo,
S., Carvalho, T., Naslund, M., and R. Gold, "Impact of
Operating Systems on Wireless Sensor Networks (Security)
Applications and Testbeds", International Conference on
Computer Communication Networks (ICCCN'2010) / IEEE
International Workshop on Wireless Mesh and Ad Hoc
Networks (WiMAN 2010) , 2010.
[wiselib] Baumgartner, T., Chatzigiannakis, I., Fekete, S., Koninis,
C., Kroller, A., and A. Pyrgelis, "Wiselib", 2010,
<www.wiselib.org/>.
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[Withings]
Withings, "The Withings scale", February 2012,
<http://www.withings.com/en/bodyscale>.
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Appendix A. Acknowledgments
The authors would like to thank Mats Naslund, Salvatore Loreto, Bob
Moskowitz, Oscar Novo, Vlasios Tsiatsis, Daoyuan Li, Muhammad Waqas,
Eric Rescorla and Tero Kivinen for interesting discussions in this
problem space. The authors would also like to thank Diego Aranha for
helping with the relic-toolkit configurations and Tobias Baumgartner
for helping with questions regarding wiselib.
Tim Chown, Samita Chakrabarti, Christian Huitema, Dan Romascanu, Eric
Vyncke, and Emmanuel Baccelli provided valuable comments that helped
us improve the final version of this document.
Authors' Addresses
Mohit Sethi
Ericsson
Jorvas 02420
Finland
EMail: mohit@piuha.net
Jari Arkko
Ericsson
Jorvas 02420
Finland
EMail: jari.arkko@piuha.net
Ari Keranen
Ericsson
Jorvas 02420
Finland
EMail: ari.keranen@ericsson.com
Heidi-Maria Back
Nokia
Helsinki 00181
Finland
EMail: heidi.back@nokia.com
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