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Practical Considerations and Implementation Experiences in Securing Smart Object Networks

The information below is for an old version of the document.
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This is an older version of an Internet-Draft that was ultimately published as RFC 8387.
Authors Mohit Sethi , Jari Arkko , Ari Keränen , Heidi-Maria Back
Last updated 2017-07-26 (Latest revision 2017-02-10)
Replaces draft-aks-lwig-crypto-sensors
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IESG IESG state Became RFC 8387 (Informational)
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Light-Weight Implementation Guidance                            M. Sethi
Internet-Draft                                                  J. Arkko
Intended status: Informational                                A. Keranen
Expires: January 26, 2018                                       Ericsson
                                                                 H. Back
                                                           July 25, 2017

  Practical Considerations and Implementation Experiences in Securing
                         Smart Object Networks


   This memo describes challenges associated with securing resource-
   constrained smart object devices.  The memo describes a possible
   deployment model suitable for these environments, discusses the
   availability of cryptographic libraries for small devices, and
   presents some preliminary experiences in implementing cryptography on
   small devices using those libraries.  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
   provisions of BCP 78 and BCP 79.

   Internet-Drafts are working documents of the Internet Engineering
   Task Force (IETF).  Note that other groups may also distribute
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   Internet-Drafts are draft documents valid for a maximum of six months
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   material or to cite them other than as "work in progress."

   This Internet-Draft will expire on January 26, 2018.

Copyright Notice

   Copyright (c) 2017 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
   ( in effect on the date of

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   publication of this document.  Please review these documents
   carefully, as they describe your rights and restrictions with respect
   to this document.  Code Components extracted from this document must
   include Simplified BSD License text as described in Section 4.e of
   the Trust Legal Provisions and are provided without warranty as
   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  . . . . . . . . . . . . . . . . . . . . . . . .   6
   6.  Protocol Architecture . . . . . . . . . . . . . . . . . . . .   8
   7.  Code Availability . . . . . . . . . . . . . . . . . . . . . .   9
   8.  Implementation Experiences  . . . . . . . . . . . . . . . . .  10
   9.  Example Application . . . . . . . . . . . . . . . . . . . . .  17
   10. Design Trade-Offs . . . . . . . . . . . . . . . . . . . . . .  20
   11. Feasibility . . . . . . . . . . . . . . . . . . . . . . . . .  20
   12. Freshness . . . . . . . . . . . . . . . . . . . . . . . . . .  21
   13. Layering  . . . . . . . . . . . . . . . . . . . . . . . . . .  23
   14. Symmetric vs. Asymmetric Crypto . . . . . . . . . . . . . . .  25
   15. Security Considerations . . . . . . . . . . . . . . . . . . .  25
   16. IANA Considerations . . . . . . . . . . . . . . . . . . . . .  25
   17. Informative references  . . . . . . . . . . . . . . . . . . .  26
   Appendix A.  Acknowledgments  . . . . . . . . . . . . . . . . . .  31
   Authors' Addresses  . . . . . . . . . . . . . . . . . . . . . . .  31

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 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 in smart object networking

   Section 7 discusses the availability of cryptographic libraries.
   Section 8 presents some experiences in implementing cryptography on
   small devices using those libraries, including information about
   achievable code sizes and speeds on typical hardware.

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   Finally, Section 10 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.  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 small 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].

   [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 all 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.

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   [I-D.irtf-t2trg-iot-seccons] discusses the overall security problem
   for Internet of Things devices.  It also discusses various solutions,
   including IKEv2/IPsec [RFC7296], TLS/SSL [RFC5246], DTLS [RFC6347],
   HIP [RFC7401] [I-D.moskowitz-hip-dex], PANA [RFC5191], and EAP
   [RFC3748].  The draft also discusses various operational scenarios,
   and challenges associated with implementing security mechanisms in
   these environments.

   [I-D.sarikaya-t2trg-sbootstrapping] discusses bootstrapping
   mechanisms available for resource-constrained IoT devices.

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 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.  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.

   The second challenge relates to practical provisioning problems.
   These are perhaps the most fundamental and difficult issue, and

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   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

   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  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

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)

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   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

5.  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
   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

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   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
   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.  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
   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.

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   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
   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:

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   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
   processor with a clock speed of 16 MHz, 2 kB of RAM, and 32 kB of
   flash memory.  Our choice of 8-bit platform may be surprising since

   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

   Here is the set of libraries we found:

   o  AvrCryptolib [avr-cryptolib]: This library provides a variety of
      different symmetric key algorithms such as AES, triple DES and
      SkipJack.  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

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      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.

   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 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 by the authors 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

   o  ARM mbed OS [mbed]: The ARM mbed operating system provides various
      cryptographic primitives that are necessary for SSL/TLS protocol
      implementation as well as X509 certificate handling.  The library
      provides an intuitive API for developer with a minimal code
      foodprint.  It is intended for various ARM platforms such as ARM
      Cortex M0, ARM Cortex M0+ and ARM Cortex M3.

   This is by no ways an exhaustive list and there exist other
   cryptographic libraries targeting resource-constrained devices.

8.  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 9 required only the

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   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
   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 |                     1,280 |

                   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 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.
   These results were obtained by turning on all the optimizations and
   using assembly code where available.  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

                                  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 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. We decided to use the Arduino Mega which has the
   same 8-bit architecture like the Arduino Uno but has a much larger
   RAM/ROM for testing 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)        |                 |
   | NIST K163       |          261 | 2,804          |            1024 |
   | (assembly math) |              |                |                 |
   | NIST K163       |          932 | 2750           |            1024 |
   | NIST B163       |         2243 | 2444           |            1024 |
   | NIST K233       |         1736 | 3675           |            2048 |
   | NIST B233       |         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)        |                 |
   | NIST K163       |          592 | 2087           |            1024 |
   | (assembly math) |              |                |                 |
   | NIST K163       |         2950 | 2215           |            1024 |
   | NIST B163       |         3213 | 2071           |            1024 |
   | NIST K233       |         6450 | 2935           |            2048 |
   | NIST B233       |         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

   o  The Arduino board only provides pseudo random numbers with the
      random() function call.  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

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   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

   The authors 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

                                  Table 8

   The authors also measured the RAM consumption by calculating the heap
   consumed for the cryptographic operations using a custom memory
   allocation handler.  The authors 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 23,216,241 cycles on the same microcontroller that
   we used for our evaluations (Arduino Mega ATmega2560).  This
   corresponds to about 14510 milliseconds of execution time.  When

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   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

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 publish-
   subscribe brokers [I-D.ietf-core-coap-pubsub] 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

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   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

   We constructed a system with four entities:


      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.


      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

   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

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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 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.
   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 publish-subscribe broker was configured
   into the smart object sensor by hardcoding the IP address.

   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
   important to note that this was only a research prototype to verify
   the feasibility of this architecture and as stated elsewhere, most

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   modern development boards have a 32-bit microcontroller since they
   are more economical and have better energy efficiency.

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.

   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.
   The authors do not expect the flash memory size 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 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:

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   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 send or receive 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.

12.  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.

   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

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   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
   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.

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   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.

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

      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

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   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

   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

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      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
   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 8, 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 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.

   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.

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17.  Informative references

              Arduino, "Arduino Uno", September 2015,

              Tschofenig, H. and M. Pegourie-Gonnard, "Performance
              Investigations", March 2015,

              AVR-CRYPTO-LIB, "AVR-CRYPTO-LIB", September 2015,

              Van der Laan, E., "AVR CRYPTOLIB", September 2015,

   [avrora]   Titzer, Ben., "Avrora", September 2015,

              NXP, "Freescale FRDM-KL25Z", June 2017,

   [huang]    Huang, C., "Low-overhead freshness transmission in sensor
              networks", 2008.

              Arkko, J. and A. Keranen, "CoAP Security Architecture",
              draft-arkko-core-security-arch-00 (work in progress), July

              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.

              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.

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              Koster, M., Keranen, A., and J. Jimenez, "Publish-
              Subscribe Broker for the Constrained Application Protocol
              (CoAP)", draft-ietf-core-coap-pubsub-02 (work in
              progress), July 2017.

              Shelby, Z., Koster, M., Bormann, C., Stok, P., and C.
              Amsuess, "CoRE Resource Directory", draft-ietf-core-
              resource-directory-11 (work in progress), July 2017.

              Jennings, C., Shelby, Z., Arkko, J., Keranen, A., and C.
              Bormann, "Media Types for Sensor Measurement Lists
              (SenML)", draft-ietf-core-senml-10 (work in progress),
              July 2017.

              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-04 (work in
              progress), June 2017.

              Moskowitz, R. and R. Hummen, "HIP Diet EXchange (DEX)",
              draft-moskowitz-hip-dex-05 (work in progress), January

              Sarikaya, B., Sethi, M., and A. Sangi, "Secure IoT
              Bootstrapping: A Survey", draft-sarikaya-t2trg-
              sbootstrapping-03 (work in progress), February 2017.

              PeerSec Networks, "Matrix SSL", September 2015,

   [mbed]     ARM, "mbed TLS", May 2017,

              MicroNaCl, "The Networking and Cryptography library for
              microcontrollers", <>.

   [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.

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   [nacl]     NaCl, "Networking and Cryptography library",

   [naclavr]  Hutter, M. and P. Schwabe, "NaCl on 8-Bit AVR
              Microcontrollers", International Conference on Cryptology
              in Africa , Springer Berlin Heidelberg , 2013.

   [nordic]   Nordic Semiconductor, "nRF52832 Product Specification",
              June 2017, <

              Aranha, D. and C. Gouv, "Relic Toolkit", September 2015,

   [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,

   [RFC3972]  Aura, T., "Cryptographically Generated Addresses (CGA)",
              RFC 3972, DOI 10.17487/RFC3972, March 2005,

   [RFC4303]  Kent, S., "IP Encapsulating Security Payload (ESP)",
              RFC 4303, DOI 10.17487/RFC4303, December 2005,

   [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, <>.

   [RFC5246]  Dierks, T. and E. Rescorla, "The Transport Layer Security
              (TLS) Protocol Version 1.2", RFC 5246,
              DOI 10.17487/RFC5246, August 2008,

   [RFC5406]  Bellovin, S., "Guidelines for Specifying the Use of IPsec
              Version 2", BCP 146, RFC 5406, DOI 10.17487/RFC5406,
              February 2009, <>.

   [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,

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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, <>.

   [RFC6347]  Rescorla, E. and N. Modadugu, "Datagram Transport Layer
              Security Version 1.2", RFC 6347, DOI 10.17487/RFC6347,
              January 2012, <>.

   [RFC6574]  Tschofenig, H. and J. Arkko, "Report from the Smart Object
              Workshop", RFC 6574, DOI 10.17487/RFC6574, April 2012,

   [RFC6690]  Shelby, Z., "Constrained RESTful Environments (CoRE) Link
              Format", RFC 6690, DOI 10.17487/RFC6690, August 2012,

   [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,

   [RFC7252]  Shelby, Z., Hartke, K., and C. Bormann, "The Constrained
              Application Protocol (CoAP)", RFC 7252,
              DOI 10.17487/RFC7252, June 2014,

   [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, <>.

   [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,

   [RFC7515]  Jones, M., Bradley, J., and N. Sakimura, "JSON Web
              Signature (JWS)", RFC 7515, DOI 10.17487/RFC7515, May
              2015, <>.

   [RFC7748]  Langley, A., Hamburg, M., and S. Turner, "Elliptic Curves
              for Security", RFC 7748, DOI 10.17487/RFC7748, January
              2016, <>.

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   [RFC7815]  Kivinen, T., "Minimal Internet Key Exchange Version 2
              (IKEv2) Initiator Implementation", RFC 7815,
              DOI 10.17487/RFC7815, March 2016,

   [RFC8032]  Josefsson, S. and I. Liusvaara, "Edwards-Curve Digital
              Signature Algorithm (EdDSA)", RFC 8032,
              DOI 10.17487/RFC8032, January 2017,

   [RFC8152]  Schaad, J., "CBOR Object Signing and Encryption (COSE)",
              RFC 8152, DOI 10.17487/RFC8152, July 2017,

              Gura, N., Patel, A., Wander, A., Eberle, H., and S.
              Shantz, "Comparing Elliptic Curve Cryptography and RSA on
              8-bit CPUs", 2010.

              Koc, C., "High-Speed RSA Implementation", November 1994,

              STMicroelectronics, "NUCLEO-F091RC", June 2017,

   [tinyecc]  North Carolina State University and North Carolina State
              University, "TinyECC", 2008,

   [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,

              Withings, "The Withings scale", February 2012,

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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
   Jorvas  02420


   Jari Arkko
   Jorvas  02420


   Ari Keranen
   Jorvas  02420


   Heidi-Maria Back
   Helsinki  00181


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