Internet DRAFT - draft-aks-lwig-crypto-sensors
draft-aks-lwig-crypto-sensors
Light-Weight Implementation Guidance M. Sethi
Internet-Draft J. Arkko
Intended status: Informational A. Keranen
Expires: April 9, 2016 H. Back
Ericsson
October 7, 2015
Practical Considerations and Implementation Experiences in Securing
Smart Object Networks
draft-aks-lwig-crypto-sensors-00
Abstract
This memo describes challenges associated with securing smart object
devices in constrained implementations and environments. The memo
describes a possible deployment model suitable for these
environments, discusses the availability of cryptographic libraries
for small devices, presents some preliminary experiences in
implementing small devices using those libraries, and discusses
trade-offs involving different types of 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 April 9, 2016.
Copyright Notice
Copyright (c) 2015 IETF Trust and the persons identified as the
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carefully, as they describe your rights and restrictions with respect
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described in the Simplified BSD License.
Table of Contents
1. Introduction . . . . . . . . . . . . . . . . . . . . . . . . 2
2. Related Work . . . . . . . . . . . . . . . . . . . . . . . . 3
3. Challenges . . . . . . . . . . . . . . . . . . . . . . . . . 4
4. Proposed Deployment Model . . . . . . . . . . . . . . . . . . 5
5. Provisioning . . . . . . . . . . . . . . . . . . . . . . . . 5
6. Protocol Architecture . . . . . . . . . . . . . . . . . . . . 8
7. Code Availability . . . . . . . . . . . . . . . . . . . . . . 8
8. Implementation Experiences . . . . . . . . . . . . . . . . . 10
9. Example Application . . . . . . . . . . . . . . . . . . . . . 16
10. Design Trade-Offs . . . . . . . . . . . . . . . . . . . . . . 19
11. Feasibility . . . . . . . . . . . . . . . . . . . . . . . . . 19
12. Freshness . . . . . . . . . . . . . . . . . . . . . . . . . . 20
13. Layering . . . . . . . . . . . . . . . . . . . . . . . . . . 22
14. Symmetric vs. Asymmetric Crypto . . . . . . . . . . . . . . . 24
15. Security Considerations . . . . . . . . . . . . . . . . . . . 25
16. IANA Considerations . . . . . . . . . . . . . . . . . . . . . 25
17. References . . . . . . . . . . . . . . . . . . . . . . . . . 25
17.1. Normative references . . . . . . . . . . . . . . . . . . 25
17.2. Informative references . . . . . . . . . . . . . . . . . 26
Appendix A. Acknowledgments . . . . . . . . . . . . . . . . . . 30
Authors' Addresses . . . . . . . . . . . . . . . . . . . . . . . 30
1. Introduction
This memo describes challenges associated with securing smart object
devices in constrained implementations and environments (see
Section 3).
Secondly, Section 4 discusses a deployment model that the authors are
considering for constrained environments. The model requires minimal
amount of configuration, and we believe it is a natural fit with the
typical communication practices smart object networking environments.
Thirdly, Section 7 discusses the availability of cryptographic
libraries. Section 8 presents some experiences in implementing small
devices using those libraries, including information about achievable
code sizes and speeds on typical hardware.
Finally, Section 10 discusses trade-offs involving different types of
security approaches.
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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. CoAP base specification [RFC7252] outlines how to
use DTLS [RFC6347] and IPsec [RFC7296] for securing the protocol.
DTLS can be applied with group keys, pairwise shared keys, or with
certificates. The security model in all cases is mutual
authentication, so while there is some commonality to HTTP in
verifying the server identity, in practice the models are quite
different. The specification says little about how DTLS keys are
managed. The IPsec mode is described with regards to the protocol
requirements, noting that small implementations of IKEv2 exist
[I-D.ietf-lwig-ikev2-minimal]. However, the specification is silent
on policy and other aspects that are normally necessary in order to
implement interoperable use of IPsec in any environment [RFC5406].
[RFC6574] gives an overview of the security discussions at the March
2011 IAB workshop on smart objects. The workshop recommended that
additional work is needed in developing suitable credential
management mechanisms (perhaps something similar to the Bluetooth
pairing mechanism), understanding the implementability of standard
security mechanisms in small 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 IP layer 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.
[I-D.garcia-core-security] discusses the overall security problem for
Internet of Things devices. It also discusses various solutions,
including IKEv2/IPsec [RFC7296], TLS/SSL [RFC5246], DTLS [RFC6347],
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HIP [RFC7401] [I-D.moskowitz-hip-dex], PANA [RFC5191], and EAP
[RFC3748]. The draft also discusses various operational scenarios,
bootstrapping mechanisms, and challenges associated with implementing
security mechanisms in these environments.
3. Challenges
This section discusses three challenges: implementation difficulties,
practical provisioning problems, and layering and communication
models.
The most often discussed issues in the security for the Internet of
Things relate to implementation difficulties. The desire to build
small, 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. Also, the use of the most
lightweight algorithms and cryptographic primitives is useful, but
should not be the only consideration in the design. 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.
The second challenge relates to practical provisioning problems.
These are 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 Small 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).
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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 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.
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.
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) [RFC5201]. 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.
5. Provisioning
As provisioning security credentials, shared secrets, and policy
information is difficult, 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.
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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 amount of configuration information
is minimized: just one short identity value needs to be fed in. Not
both an identity and a certificate. Not 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. When both peers know the expected
cryptographic identity of the other peer 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. 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 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. The authors have employed a 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
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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 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.
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. 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).
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
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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 Igrp.
6. 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
transmissions. While this is not impossible in data object security
solutions either, it is not the typical arrangement either.
7. 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
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processor with a clock speed of 16 MHz, 2 kB of SRAM, and 32 kB of
flash memory.
For selecting potential asymmetric cryptographic libraries, we did an
extensive survey 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. Please 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 a variety of
different symmetric key algorithms such as DES/Triple DES/AES etc.
and RSA as an asymmetric key algorithm. We stripped down the
library to use only the required RSA components and used a
separate SHA-256 implementation from the original AvrCrypto-Lib
library [avr-crypto-lib]. Parts of SHA-256 and RSA algorithm
implementations were written in AVR-8 bit assembly language to
reduce the size and optimize the performance. The library also
takes advantage of the fact that Arduino boards allow the
programmer to directly address the flash memory to access constant
data which can save the amount of SRAM used during execution.
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
and many more. The toolkit provides an option to build only the
desired components for the required platform. While building the
library, it is possible to select a variety mathematical
optimizations that can be combined to obtain the desired
performance (as a general thumb rule, faster implementations
require more SRAM and flash). It includes a multi precision
integer math module which can be customized to use different bit-
length words.
o TinyECC [tinyecc]: TinyECC was designed for using Elliptic Curve
based public key cryptography on sensor networks. It is written
in nesC programming language and as such is designed for specific
use on TinyOS. However, the library can be ported to standard C99
either with hacked tool-chains or manually rewriting parts of the
code. This allows for the library to be used on platforms that do
not have TinyOS running on them. The library includes a wide
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variety of mathematical optimizations such as sliding window,
Barrett reduction for verification, precomputation, etc. It also
has one of the smallest memory footprints among the set of
Elliptic Curve libraries surveyed so far. However, an advantage
of Relic over TinyECC is that it can do curves over binary fields
in addition to prime fields.
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 by the authors to
test the code on Arduino Uno. The structure of the code is similar
to TinyECC and like TinyECC it implements elliptic curves over
prime fields only. In order to make the code platform
independent, no assembly level optimizations were incorporated.
Since efficiency was not an important goal for the authors of the
library while designing, many well known theoretical performance
enhancement features were also not incorporated. Like the relic-
toolkit, Wiselib is also Lesser GPL licensed.
o MatrixSSL [matrix-ssl]: This library provides a low footprint
implementation of several cryptographic algorithms including RSA
and ECC (with a commercial license). However, the library in the
original form takes about 50 kB of ROM which is not suitable for
our hardware requirements. Moreover, it is intended for 32-bit
systems and the API includes functions for SSL communication
rather than just signing data with private keys.
This is by no ways an exhaustive list and there exist other
cryptographic libraries targeting resource-constrained devices.
8. Implementation Experiences
We have summarized the initial results of RSA private key performance
using AvrCryptolib 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 keys were generated separately and were hard
coded into the program. All keys were generated with the value of
the public exponent as 3. The performance of signing with private
key was faster for smaller key lengths as was expected. However the
increase in the execution time was considerable when the key size was
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2048 bits. It is important to note that two different sets of
experiments were performed for each key length. In the first case,
the keys were loaded into the SRAM from the ROM (flash) before they
were used by any of the functions. However, in the second case, the
keys were addressed directly in the ROM. As was expected, the second
case used less SRAM but lead to longer execution time.
More importantly, any RSA key size less than 2,048-bit should be
considered legacy and insecure. The performance measurements for
these keys are provided here for reference only.
+--------+--------------+--------------+-------------+--------------+
| Key | Execution | Memory | Execution | Memory |
| length | time (ms); | footprint | time (ms); | footprint |
| (bits) | key in SRAM | (bytes); key | key in ROM | (bytes); key |
| | | in SRAM | | in ROM |
+--------+--------------+--------------+-------------+--------------+
| 64 | 64 | 40 | 69 | 32 |
| 128 | 434 | 80 | 460 | 64 |
| 512 | 25,076 | 320 | 27,348 | 256 |
| 1,024 | 199,688 | 640 | 218,367 | 512 |
| 2,048 | 1,587,567 | 1,280 | 1,740,258 | 1,024 |
+--------+--------------+--------------+-------------+--------------+
Table 1: RSA private key operation performance
The code size was less than 3.6 kB for all the test cases with scope
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 SRAM, we believe that 1024/2048-bit
operations can be performed in much less time as has been shown in
[rsa-8bit]. 2048-bit RSA is nonetheless possible with about 1 kB of
SRAM as is seen in Table 1.
In Table 2 we present the results obtained by manually porting
TinyECC into C99 standard and running ECDSA signature algorithm on
the Arduino Uno board. TinyECC supports a variety of SEC 2
recommended Elliptic Curve domain parameters. The execution time and
memory footprint are shown next to each of the curve parameters.
SHA-1 hashing algorithm included in the library was used in each of
the cases. The measurements reflect the performance of elliptic
curve signing only and not the SHA-1 hashing algorithm. SHA-1 is now
known to be insecure and should not be used in real deployments. It
is clearly observable that for similar security levels, Elliptic
Curve public key cryptography outperforms RSA. These results were
obtained by turning on all the optimizations. These optimizations
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include - Curve Specific Optimizations for modular reduction (NIST
and SEC 2 field primes were chosen as pseudo-Mersenne primes),
Sliding Window for faster scalar multiplication, Hybrid squaring
procedure written in assembly and Weighted projective Coordinate
system for efficient scalar point addition, doubling and
multiplication. We did not use optimizations like Shamir Trick and
Sliding Window as they are only useful for signature verification and
tend to slow down the signature generation by precomputing values (we
were only interested in fast signature generation). There is still
some scope for optimization as not all the assembly code provided
with the library could be ported to Arduino directly. Re-writing
these procedures in compatible assembly would further enhance the
performance.
+-------------+---------------+-----------------+-------------------+
| Curve | Execution | Memory | Comparable RSA |
| parameters | time (ms) | Footprint | key length |
| | | (bytes) | |
+-------------+---------------+-----------------+-------------------+
| 128r1 | 1,858 | 776 | 704 |
| 128r2 | 2,002 | 776 | 704 |
| 160k1 | 2,228 | 892 | 1,024 |
| 160r1 | 2,250 | 892 | 1,024 |
| 160r2 | 2,467 | 892 | 1,024 |
| 192k1 | 3,425 | 1008 | 1,536 |
| 192r1 | 3,578 | 1008 | 1,536 |
+-------------+---------------+-----------------+-------------------+
Table 2: ECDSA signature performance with TinyECC
We also performed experiments by removing the assembly code for
hybrid multiplication and squaring thus 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 our 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.
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+-------------+---------------+-----------------+-------------------+
| Curve | Execution | Memory | Comparable RSA |
| parameters | time (ms) | Footprint | key length |
| | | (bytes) | |
+-------------+---------------+-----------------+-------------------+
| 128r1 | 2,741 | 776 | 704 |
| 128r2 | 3,086 | 776 | 704 |
| 160k1 | 3,795 | 892 | 1,024 |
| 160r1 | 3,841 | 892 | 1,024 |
| 160r2 | 4,118 | 892 | 1,024 |
| 192k1 | 6,091 | 1008 | 1,536 |
| 192r1 | 6,217 | 1008 | 1,536 |
+-------------+---------------+-----------------+-------------------+
Table 3: ECDSA signature performance with TinyECC (No assembly
optimizations)
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
obtain results for for all the 128, 160 and 192-bit SEC 2 Elliptic
curves. SHA-1 algorithm provided in the library was used. The
measurements reflect the performance of elliptic curve signing only
and not the SHA-1 hashing algorithm. SHA-1 is now known to be
insecure and should not be used in real deployments. The ROM size
for all the experiments was less than 16 kB.
+-------------+---------------+-----------------+-------------------+
| Curve | Execution | Memory | Comparable RSA |
| parameters | time (ms) | Footprint | key length |
| | | (bytes) | |
+-------------+---------------+-----------------+-------------------+
| 128r1 | 5,615 | 732 | 704 |
| 128r2 | 5,615 | 732 | 704 |
| 160k1 | 10,957 | 842 | 1,024 |
| 160r1 | 10,972 | 842 | 1,024 |
| 160r2 | 10,971 | 842 | 1,024 |
| 192k1 | 18,814 | 952 | 1,536 |
| 192r1 | 18,825 | 952 | 1,536 |
+-------------+---------------+-----------------+-------------------+
Table 4: ECDSA signature performance with Wiselib
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. We decided to use the Arduino Mega which has the
same 8-bit architecture like the Arduino Uno but has a much larger
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RAM/ROM for testing relic-toolkit. Again, SHA-1 hashing algorithm
included in the library was used in each of the cases. The
measurements reflect the performance of elliptic curve signing only
and not the SHA-1 hashing algorithm. SHA-1 is now known to be
insecure and should not be used in real deployments. The library
does provide several alternatives with such as SHA-256.
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
crypto 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
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) | |
+-----------------+--------------+----------------+-----------------+
| NIST K163 | 261 | 2,804 | 1024 |
| (assembly math) | | | |
| NIST K163 | 932 | 2,750 | 1024 |
| NIST B163 | 2,243 | 2,444 | 1024 |
| NIST K233 | 1,736 | 3,675 | 2,048 |
| NIST B233 | 4,471 | 3,261 | 2,048 |
+-----------------+--------------+----------------+-----------------+
Table 5: ECDSA signature performance with relic-toolkit (Fast)
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+-----------------+--------------+----------------+-----------------+
| Curve | Execution | Memory | Comparable RSA |
| parameters | time (ms) | Footprint | key length |
| | | (bytes) | |
+-----------------+--------------+----------------+-----------------+
| NIST K163 | 592 | 2,087 | 1024 |
| (assembly math) | | | |
| NIST K163 | 2,950 | 2,215 | 1024 |
| NIST B163 | 3,213 | 2,071 | 1024 |
| NIST K233 | 6,450 | 2,935 | 2,048 |
| NIST B233 | 6,100 | 2,737 | 2,048 |
+-----------------+--------------+----------------+-----------------+
Table 6: ECDSA signature performance with relic-toolkit (Low Memory)
It is important to note the following points about the elliptic curve
measurements:
o As with the RSA measurements, curves giving less that 112-bit
security are insecure and considered as legacy. The measurements
are only provided for reference.
o The arduino board only provides pseudo random numbers with the
random() function call. In order to create private keys with a
better quality of random number, we can use a true random number
generator like the one provided by TrueRandom library
[truerandom], or create the keys separately on a system with a
true random number generator and then use them directly in the
code.
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.
A summary library ROM use is shown in Table 7.
+---------------+---------------------------+
| Library | ROM Footprint (Kilobytes) |
+---------------+---------------------------+
| AvrCryptolib | 3.6 |
| Wiselib | 16 |
| TinyECC | 18 |
| Relic-toolkit | 29 |
+---------------+---------------------------+
Table 7: Summary of library ROM needs
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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.
9. 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 be 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 mirror
proxies [I-D.vial-core-mirror-proxy] instead. Architecturally, the
idea is that sensors can delegate a part of 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 mirror proxies, 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 mirror proxy, and periodically
update the readings. All queries from the rest of the world go to
the mirror proxy.
We constructed a system with four entities:
Sensor
This is an Arduino-based device that runs a CoAP mirror proxy
client and Relic-toolkit. Relic takes 29 Kbytes of ROM, and the
simple CoAP client roughly 3 kilobytes.
Mirror Proxy
This is a mirror proxy that holds resources on the sensor's
behalf. The sensor registers itself to this node.
Resource Directory
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While physically in the same node in our implementation, a
resource directory is a logical function that allows sensors and
mirror proxies 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 mirror proxy.
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 mirror proxy. 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 sensor reading update to the
mirror proxy it signs the message contents with a JOSE signature on
the used JSON/SENML payload [RFC7515] [I-D.jennings-core-senml].
In Step 3, any other device in the network -- including the mirror
proxy, 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 Mirror Proxy (MP) and the
Resource Directory (RD) reside on the same physical host. A 64-bit
x86 linux machine serves as the MP and the RD, while a similar but
physically different 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 (163-bit
Koblitz curve over binary field). While compiling Relic for our
prototype, we used the fast configuration without any assembly
optimizations.
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The gateway implements the CoAP base specification in the Java
programming language and extends it to add support for Mirror Proxy
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 SRAM
requirements and uses stack-based allocation only. It is inter-
operable with the Java implementation of CoAP running on the gateway.
The location of the mirror proxy was pre-configured into the smart
object sensor by hardcoding the IP address. We used an IPv4 network
with public IP addresses obtained from a DHCP server.
Some important statistics of this prototype are listed in table
Table 8. Our straw man analysis of the performance of this prototype
is preliminary. Our intention was to demonstrate the feasibility of
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 SRAM
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.
+-----------------------------------------------------------+-------+
| Flash memory consumption (for the entire prototype | 51 kB |
| including Relic crypto + CoAP + Arduino UDP, Ethernet and | |
| DHCP Libraries) | |
| | |
| SRAM consumption (for the entire prototype including DHCP | 4678 |
| client + key generation + signing the hash of message + | bytes |
| COAP + UDP + Ethernet) | |
| | |
| Execution time for creating the key pair + sending | 2030 |
| registration message + time spent waiting for | ms |
| acknowledgment | |
| | |
| Execution time for signing the hash of message + sending | 987 |
| update | ms |
| | |
| Signature overhead | 42 |
| | bytes |
+-----------------------------------------------------------+-------+
Table 8: Prototype Performance
To demonstrate the efficacy of this communication model we compare it
with a scenario where the smart objects do not transition into the
energy saving sleep mode and directly serve temperature data to
clients. As an example, we assume that in our architecture, the
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smart objects wake up once every minute to report the signed
temperature data to the caching MP. If we calculate the energy
consumption using the formula W = U * I * t (where U is the operating
voltage, I is the current drawn and t is the execution time), and use
the voltage and current values from the datasheets of the ATmega2560
(20mA-active mode and 5.4mA-sleep mode) and W5100 (183mA) chips used
in the architecture, then in a one minute period, the Arduino board
would consume 60.9 Joules of energy if it directly serves data and
does not sleep. On the other hand, in our architecture it would only
consume 2.6 Joules if it wakes up once a minute to update the MP with
signed data. Therefore, a typical Li-ion battery that provides about
1800 milliamps per hour (mAh) at 5V would have a lifetime of 9 hours
in the unsecured always-on scenario, whereas it would have a lifetime
of about 8.5 days in the secured sleepy architecture presented.
These lifetimes appear to be low because the Arduino board in the
prototype uses Ethernet which is not energy efficient. The values
presented only provide an estimate (ignoring the energy required to
transition in and out of the sleep mode) and would vary depending on
the hardware and MAC protocol used. Nonetheless, it is evident that
our architecture can increase the life of smart objects by allowing
them to sleep and can ensure security at the same time.
10. 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. This analysis looks at layering and the choice of
symmetric vs. asymmetric cryptography.
11. Feasibility
The first question is whether using cryptographic security and
asymmetric cryptography in particular is feasible at all on small
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
small and difficult as possible.
In reality, ROM memory size is probably easier to grow than other
parameters in microcontrollers. 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. In short, the authors do not expect the code size to
be a significant limiting factor, both because of the small amount of
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code that is needed and because available memory space is growing
rapidly.
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 for the
computation of a signature for the message that it is about to send.
Or even spend multiple seconds in some cases. 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
this is too long. Nevertheless, the authors believe that these
algorithms can successfully be employed in small devices for the
following reasons:
o With the right selection of algorithms and libraries, the
execution times can actually be smaller. Using the Relic-toolkit
with the NIST K163 algorithm (roughly equivalent to RSA at 1024
bits) at 0.3 seconds is a good example of this.
o As discussed in [wiman], in general the power requirements
necessary to send or receive messages are far bigger than those
needed to execute cryptographic operations. There is no good
reason to choose platforms that do not provide sufficient
computing power to run the necessary 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 paper.
o Using public key cryptography only at the beginning of a session
will reduce the per-packet processing times significantly.
12. Freshness
In our architecture, if implemented as described thus far, messages
along with their signatures sent from the sensors to the mirror proxy
can be recorded and replayed by an eavesdropper. The mirror proxy
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:
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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.
o Network time synchronization protocols such as Network Time
Protocol (NTP) [RFC1305] 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 mirror proxy 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 mirror proxy 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
mirror proxy can still end up in a discordant state where the
sequence number received by the mirror proxy 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 mirror
proxy 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 mirror
proxy if a reset message is received. The sensors re-synchronize by
sending a new registration message with the current sequence number.
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Although sequence numbers protect the system from replay attacks, a
mirror proxy 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 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
mirror proxy to determine the time when the update was created. For
example, when the mirror proxy 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
mirror proxy 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 mirror proxy 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 mirror proxy 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 [RFC1305]. The smart objects could also
have access to a GSM 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 mirror
proxy 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.
13. 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
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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.
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
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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
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. The authors believe 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.
14. 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
crypto 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 8, the time needed to calculate some
of the asymmetric crypto 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
small 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.
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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.
15. Security Considerations
This entire memo deals with security issues.
16. IANA Considerations
There are no IANA impacts in this memo.
17. References
17.1. Normative references
[arduino-uno]
"Arduino Uno", September 2015,
<http://arduino.cc/en/Main/arduinoBoardUno>.
[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/>.
[huang] Huang, C., "Low-overhead freshness transmission in sensor
networks", 2008.
[matrix-ssl]
PeerSec Networks, "Matrix SSL", September 2015,
<http://www.matrixssl.org/>.
[relic-toolkit]
Aranha, D. and C. Gouv, "Relic Toolkit", September 2015,
<http://code.google.com/p/relic-toolkit/>.
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[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>.
[tinyecc] North Carolina State University and North Carolina State
University, "TinyECC", 2008,
<http://discovery.csc.ncsu.edu/software/TinyECC/>.
[truerandom]
Drow, C., "Truerandom", September 2015,
<http://code.google.com/p/tinkerit/wiki/TrueRandom>.
[wiselib] Baumgartner, T., Chatzigiannakis, I., Fekete, S., Koninis,
C., Kroller, A., and A. Pyrgelis, "Wiselib", 2010,
<www.wiselib.org/>.
17.2. Informative references
[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.garcia-core-security]
Garcia-Morchon, O., Kumar, S., Keoh, S., Hummen, R., and
R. Struik, "Security Considerations in the IP-based
Internet of Things", draft-garcia-core-security-06 (work
in progress), September 2013.
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[I-D.ietf-core-resource-directory]
Shelby, Z., Koster, M., Bormann, C., and P. Stok, "CoRE
Resource Directory", draft-ietf-core-resource-directory-04
(work in progress), July 2015.
[I-D.ietf-lwig-ikev2-minimal]
Kivinen, T., "Minimal IKEv2 Initiator Implementation",
draft-ietf-lwig-ikev2-minimal-04 (work in progress),
September 2015.
[I-D.jennings-core-senml]
Jennings, C., Shelby, Z., Arkko, J., and A. Keranen,
"Media Types for Sensor Markup Language (SENML)", draft-
jennings-core-senml-01 (work in progress), July 2015.
[I-D.moskowitz-hip-dex]
Moskowitz, R. and R. Hummen, "HIP Diet EXchange (DEX)",
draft-moskowitz-hip-dex-04 (work in progress), July 2015.
[I-D.vial-core-mirror-proxy]
Vial, M., "CoRE Mirror Server", draft-vial-core-mirror-
proxy-01 (work in progress), July 2012.
[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", 2010.
[RFC1305] Mills, D., "Network Time Protocol (Version 3)
Specification, Implementation and Analysis", RFC 1305,
DOI 10.17487/RFC1305, March 1992,
<http://www.rfc-editor.org/info/rfc1305>.
[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,
<http://www.rfc-editor.org/info/rfc3748>.
[RFC3972] Aura, T., "Cryptographically Generated Addresses (CGA)",
RFC 3972, DOI 10.17487/RFC3972, March 2005,
<http://www.rfc-editor.org/info/rfc3972>.
[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, <http://www.rfc-editor.org/info/rfc5191>.
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[RFC5201] Moskowitz, R., Nikander, P., Jokela, P., Ed., and T.
Henderson, "Host Identity Protocol", RFC 5201,
DOI 10.17487/RFC5201, April 2008,
<http://www.rfc-editor.org/info/rfc5201>.
[RFC5246] Dierks, T. and E. Rescorla, "The Transport Layer Security
(TLS) Protocol Version 1.2", RFC 5246,
DOI 10.17487/RFC5246, August 2008,
<http://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, <http://www.rfc-editor.org/info/rfc5406>.
[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, <http://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, <http://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,
<http://www.rfc-editor.org/info/rfc6574>.
[RFC6690] Shelby, Z., "Constrained RESTful Environments (CoRE) Link
Format", RFC 6690, DOI 10.17487/RFC6690, August 2012,
<http://www.rfc-editor.org/info/rfc6690>.
[RFC7252] Shelby, Z., Hartke, K., and C. Bormann, "The Constrained
Application Protocol (CoAP)", RFC 7252,
DOI 10.17487/RFC7252, June 2014,
<http://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, <http://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,
<http://www.rfc-editor.org/info/rfc7401>.
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[RFC7515] Jones, M., Bradley, J., and N. Sakimura, "JSON Web
Signature (JWS)", RFC 7515, DOI 10.17487/RFC7515, May
2015, <http://www.rfc-editor.org/info/rfc7515>.
[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. In International Conference on
Computer Communication Networks (ICCCN'2010) / IEEE
International Workshop on Wireless Mesh and Ad Hoc
Networks (WiMAN 2010), 2010, Zurich. Proceedings of
ICCCN'2010/WiMAN'2010", 2010.
[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.
Authors' Addresses
Mohit Sethi
Ericsson
Jorvas 02420
Finland
EMail: mohit.m.sethi@ericsson.com
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
Ericsson
Jorvas 02420
Finland
EMail: heidi-maria.back@ericsson.com
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