path: root/doc/rfc/rfc8387.txt

Internet Engineering Task Force (IETF)                          M. Sethi
Request for Comments: 8387                                      J. Arkko
Category: Informational                                       A. Keranen
ISSN: 2070-1721                                                 Ericsson
                                                                 H. Back
                                                                   Nokia
                                                                May 2018


       Practical Considerations and Implementation Experiences in
                     Securing Smart Object Networks

Abstract

   This memo describes challenges associated with securing resource-
   constrained smart object devices.  The memo describes a possible
   deployment model where resource-constrained devices sign message
   objects, discusses the availability of cryptographic libraries for
   resource-constrained devices, and presents some preliminary
   experiences with those libraries for message signing on resource-
   constrained devices.  Lastly, the memo discusses trade-offs involving
   different types of security approaches.

Status of This Memo

   This document is not an Internet Standards Track specification; it is
   published for informational purposes.

   This document is a product of the Internet Engineering Task Force
   (IETF).  It represents the consensus of the IETF community.  It has
   received public review and has been approved for publication by the
   Internet Engineering Steering Group (IESG).  Not all documents
   approved by the IESG are candidates for any level of Internet
   Standard; see Section 2 of RFC 7841.

   Information about the current status of this document, any errata,
   and how to provide feedback on it may be obtained at
   https://www.rfc-editor.org/info/rfc8387.













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Copyright Notice

   Copyright (c) 2018 IETF Trust and the persons identified as the
   document authors.  All rights reserved.

   This document is subject to BCP 78 and the IETF Trust's Legal
   Provisions Relating to IETF Documents
   (https://trustee.ietf.org/license-info) in effect on the date of
   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  . . . . . . . . . . . . . . . . . . . . . . . .   3
   2.  Related Work  . . . . . . . . . . . . . . . . . . . . . . . .   3
   3.  Challenges  . . . . . . . . . . . . . . . . . . . . . . . . .   4
   4.  Proposed Deployment Model . . . . . . . . . . . . . . . . . .   6
     4.1.  Provisioning  . . . . . . . . . . . . . . . . . . . . . .   6
     4.2.  Protocol Architecture . . . . . . . . . . . . . . . . . .   9
   5.  Code Availability . . . . . . . . . . . . . . . . . . . . . .  10
   6.  Implementation Experiences  . . . . . . . . . . . . . . . . .  12
   7.  Example Application . . . . . . . . . . . . . . . . . . . . .  18
   8.  Design Trade-Offs . . . . . . . . . . . . . . . . . . . . . .  21
     8.1.  Feasibility . . . . . . . . . . . . . . . . . . . . . . .  21
     8.2.  Freshness . . . . . . . . . . . . . . . . . . . . . . . .  22
     8.3.  Layering  . . . . . . . . . . . . . . . . . . . . . . . .  24
     8.4.  Symmetric vs. Asymmetric Crypto . . . . . . . . . . . . .  26
   9.  Summary . . . . . . . . . . . . . . . . . . . . . . . . . . .  27
   10. Security Considerations . . . . . . . . . . . . . . . . . . .  27
   11. IANA Considerations . . . . . . . . . . . . . . . . . . . . .  27
   12. Informative References  . . . . . . . . . . . . . . . . . . .  27
   Acknowledgments . . . . . . . . . . . . . . . . . . . . . . . . .  33
   Authors' Addresses  . . . . . . . . . . . . . . . . . . . . . . .  33














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1.  Introduction

   This memo describes challenges associated with securing smart object
   devices in constrained implementations and environments.  In
   Section 3, we specifically discuss three challenges: the
   implementation difficulties encountered on resource-constrained
   platforms, the problem of provisioning keys, and making the choice of
   implementing security at the appropriate layer.

   Section 4 discusses a potential deployment model for constrained
   environments.  The model requires a minimal amount of configuration,
   and we believe it is a natural fit with the typical communication
   practices in smart object networking environments.

   Section 5 discusses the availability of cryptographic libraries.
   Section 6 presents some experiences in implementing cryptography on
   resource-constrained devices using those libraries, including
   information about achievable code sizes and speeds on typical
   hardware.  Section 7 describes an example proof-of-concept prototype
   implementation that uses public-key cryptography on resource-
   constrained devices to provide end-to-end data authenticity and
   integrity protection.

   Finally, Section 8 discusses trade-offs involving different types of
   security approaches.

2.  Related Work

   The Constrained Application Protocol (CoAP) [RFC7252] is a
   lightweight protocol designed to be used in machine-to-machine
   applications such as smart energy and building automation.  Our
   discussion uses this protocol as an example, but the conclusions may
   apply to other similar protocols.  The CoAP base specification
   [RFC7252] outlines how to use DTLS [RFC6347] and IPsec [RFC4303] for
   securing the protocol.  DTLS can be applied with pairwise shared
   keys, raw public keys, or certificates.  The security model in all
   cases is mutual authentication, so while there is some commonality to
   HTTP [RFC7230] in verifying the server identity, in practice the
   models are quite different.  The use of IPsec with CoAP is described
   with regards to the protocol requirements, noting that lightweight
   implementations of the Internet Key Exchange Protocol Version 2
   (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].

   [IoT-SECURITY] documents the different stages in the life cycle of a
   smart object.  Next, it highlights the security threats for smart
   objects and the challenges that one might face to protect against



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   these threats.  The document also looks at various security protocols
   available, including IKEv2/IPsec [RFC7296], TLS/SSL [RFC5246], DTLS
   [RFC6347], the Host Identity Protocol (HIP) [RFC7401], HIP Diet
   EXchange [HIP-DEX], a Protocol for Carrying Authentication for
   Network Access (PANA) [RFC5191], and the Extensible Authentication
   Protocol (EAP) [RFC3748].  Lastly, [IoT-BOOTSTRAPPING] discusses
   bootstrapping mechanisms available for resource-constrained Internet
   of Things (IoT) devices.

   [RFC6574] gives an overview of the security discussions at the March
   2011 IAB workshop on smart objects.  The workshop recommended that
   additional work should be undertaken in developing suitable
   credential management mechanisms (perhaps something similar to the
   Bluetooth pairing mechanism), understanding the implementability of
   standard security mechanisms in resource-constrained devices, and
   conducting additional research in the area of lightweight
   cryptographic primitives.

   [HIP-DEX] defines a lightweight 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.

   [IPV6-LOWPAN-SEC] makes a comprehensive analysis of security issues
   related to IPv6 over Low-Power Wireless Personal Area Network
   (6LoWPAN) networks, but its findings also apply more generally for
   all low-powered networks.  Some of the issues this document discusses
   include the need to minimize the number of transmitted bits and
   simplify implementations, threats in the smart object networking
   environments, and the suitability of 6LoWPAN security mechanisms,
   IPsec, and key management protocols for implementation in these
   environments.

3.  Challenges

   This section discusses three challenges: 1) implementation
   difficulties, 2) practical provisioning problems, and 3) layering and
   communication models.

   One of the most often discussed issues in the security for the
   Internet of Things relate to implementation difficulties.  The desire
   to build resource-constrained, battery-operated, and inexpensive
   devices drives the creation of devices with a limited protocol and
   application suite.  Some of the typical limitations include running
   CoAP instead of HTTP, limited support for security mechanisms,



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   limited processing power for long key lengths, a 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 most lightweight algorithms and
   cryptographic primitives are 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.
   This is perhaps the most fundamental and difficult issue and is
   unfortunately often neglected in the design.  There are several
   problems in the provisioning and management of smart object networks:

   o  Resource-constrained devices have no natural user interface for
      configuration that would be required for the installation of
      shared secrets and other security-related parameters.  Typically,
      there is no keyboard or display, and there may not even be buttons
      to press.  Some devices may only have one interface, the interface
      to the network.

   o  Manual configuration is rarely, if at all, possible, as the
      necessary skills are missing in typical installation environments
      (such as in family homes).

   o  There may be a large number of devices.  Configuration tasks that
      may be acceptable when performed for one device may become
      unacceptable with dozens or hundreds of devices.

   o  Smart object networks may rely on different radio technologies.
      Provisioning methods that rely on specific link-layer features may
      not work with other radio technologies in a heterogeneous network.






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   o  Network configurations evolve over the lifetime of the devices, as
      additional devices are introduced or addresses change.  Various
      central nodes may also receive more frequent updates than
      individual devices such as sensors embedded in building materials.

   In light of the above challenges, resource-constrained devices are
   often shipped with a single static identity.  In many cases, it is a
   single raw public key.  These long-term static identities makes it
   easy to track the devices (and their owners) when they move.  The
   static identities may also allow an attacker to track these devices
   across ownership changes.

   Finally, layering and communication models present difficulties for
   straightforward use of the most obvious security mechanisms.  Smart
   object networks typically pass information through multiple
   participating nodes [CoAP-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 relate 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

   [CoAP-SECURITY] recognizes the provisioning model as the driver of
   what kind of security architecture is useful.  This section
   reintroduces this model briefly here in order to facilitate the
   discussion of the various design alternatives later.

   The basis of the proposed architecture are self-generated secure
   identities, similar to Cryptographically Generated Addresses (CGAs)
   [RFC3972] or Host Identity Tags (HITs) [RFC7401].  That is, we assume
   the following holds:

      I = h(P|O)

   where I is the secure identity of the device, h is a hash function, P
   is the public key from a key pair generated by the device, and O is
   optional other information. "|" (vertical bar) here denotes the
   concatenation operator.

4.1.  Provisioning

   As it is difficult to provision security credentials, shared secrets,
   and policy information, the provisioning model is based only on the
   secure identities.  A typical network installation involves physical
   placement of a number of devices while noting the identities of these
   devices.  This list of short identifiers can then be fed to a central
   server as a list of authorized devices.  Secure communications can



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   then commence with the devices, at least as far as information 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 a large number of devices to a 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; however, 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 a separate user interface, a local
   connection (such as USB), or use of 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
   certificate or shared secrets that must be kept confidential).  An
   even simpler provisioning approach is that the devices in the device
   group trust each other.  Then no configuration is needed at
   installation time.

   Once both the parties interested in communicating know the expected
   cryptographic identity of the other offline, secure communications
   can commence.  Alternatively, various pairing schemes can be
   employed.  Note that these schemes can benefit from the already
   secure identifiers on the device side.  For instance, the server can
   send a pairing message to each device after their initial power-on
   and before they have been paired with anyone, encrypted with the
   public key of the device.  As with all pairing schemes that do not
   employ a shared secret or the secure identity of both parties, there
   are some remaining vulnerabilities that may or may not be acceptable
   for the application in question.  For example, many pairing methods
   based on "leap of faith" or "trust on first use" assume that the
   attacker is not present during the initial setup.  Therefore, they
   are vulnerable to eavesdropping or man-in-the-middle (MitM) attacks.

   In any case, the secure identities help again in ensuring that the
   operations are as simple as possible.  Only identities need to be
   communicated to the devices, not certificates, shared secrets, or,
   e.g., IPsec policy rules.




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   Where necessary, the information collected at installation time may
   also include other parameters relevant to the application, such as
   the location or purpose of the devices.  This would enable the server
   to know, for instance, that a particular device is the temperature
   sensor for the kitchen.

   Collecting the identity information at installation time can be
   arranged in a number of ways.  One simple but not completely secure
   method is 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 (RFID) tags.  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 needed for provisioning
   security.

   As discussed in the previous section, long-term static identities
   negatively affect the privacy of the devices and their owners.
   Therefore, it is beneficial for devices to generate new identities at
   appropriate times during their life cycle; an example is after a
   factory reset or an ownership handover.  Thus, in our proposed
   deployment model, the devices would generate a new asymmetric key
   pair and use the new public-key P' to generate the new identity I'.
   It is also desirable that these identities are only used during the
   provisioning stage.  Temporary identities (such as dynamic IPv6



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   addresses) can be used for network communication protocols once the
   device is operational.

   Groups of devices can be managed through single identifiers as well.
   In these deployment cases, it is also possible to configure the
   identity of an entire group of devices, rather than registering the
   individual devices.  For instance, many installations employ a kit of
   devices bought from the same manufacturer in one package.  It is easy
   to provide an identity for such a set of devices as follows:

      Idev = h(Pdev|Potherdev1|Potherdev2|...|Potherdevn)

      Igrp = h(Pdev1|Pdev2|...|Pdevm)

   where Idev is the identity of an individual device, Pdev is the
   public key of that device, Potherdevi are the public keys of other
   devices in the group, n is all the devices in the group except the
   device with Pdev as its public key, and m is the total number of
   devices in the group.  Now, we can define the secure identity of the
   group (Igrp) as a hash of all the public keys of the devices in the
   group (Pdevi).

   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 cannot claim to be in the group, because the
   group identity would change if any new keys were added to the
   identity of the group (Igrp).

4.2.  Protocol Architecture

   As noted above, the starting point of the architecture is that nodes
   self-generate secure identities, which are then communicated out of
   band to the peers that need to know what devices to trust.  To
   support this model in a protocol architecture, we also need to use
   these secure identities to implement secure messaging between the
   peers, explain how the system can respond to different types of
   attacks such as replay attempts, and decide 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.  [CoAP-SECURITY] 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



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   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, and 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, it is generally not the typical arrangement.

5.  Code Availability

   For implementing public-key cryptography on resource-constrained
   environments, we chose the 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 an 8-bit platform may seem surprising
   since cheaper and more energy-efficient 32-bit platforms are
   available.  However, our intention was to evaluate the performance of
   public-key cryptography on the most resource-constrained platforms
   available.  It is reasonable to expect better performance results
   from 32-bit microcontrollers.

   For selecting potential asymmetric cryptographic libraries, we
   surveyed and came up with a set of possible code sources and
   performed an initial analysis of how well they fit the Arduino
   environment.  Note that the results are preliminary and could easily
   be affected in any direction by implementation bugs, configuration
   errors, and other mistakes.  It is advisable to verify the numbers
   before relying on them for building something.  No significant effort
   was done to optimize ROM memory usage beyond what the libraries
   provided themselves, so those numbers should be taken as upper
   limits.




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   Here is the set of libraries we found:

   o  AVRCryptoLib [avr-cryptolib]: This library provides symmetric key
      algorithms such as AES.  It provides RSA as an asymmetric key
      algorithm.  Parts of the library were written in AVR 8-bit
      assembly language to reduce the size and optimize the performance.

   o  Relic-toolkit [relic-toolkit]: This library is written entirely in
      C and provides a highly flexible and customizable implementation
      of a large variety of cryptographic algorithms.  This not only
      includes RSA and ECC but also pairing-based asymmetric
      cryptography, Boneh-Lynn-Shacham signatures, and Boneh-Boyen short
      signatures.  The library has also added support for curve25519
      (for Elliptic Curve Diffie-Hellman key exchange) [RFC7748] and
      edwards25519 (for elliptic curve digital signatures) [RFC8032].
      The toolkit provides an option to build only the desired
      components for the required platform.

   o  TinyECC [tinyecc]: TinyECC was designed for using elliptic-curve-
      based public-key cryptography on sensor networks.  It is written
      in the nesC programming language [nesC] and as such is designed
      for specific use on TinyOS.  However, the library can be ported to
      standard C either with tool chains or by 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 algorithms for cryptography, localization,
      topology management, and many more.  The library was designed with
      the idea of making it easy to interface the library with operating
      systems like iSense and Contiki.  However, since the library is
      written entirely in C++ with a template-based model similar to
      Boost/CGAL, it can be used on any platform directly without using
      any of the operating system interfaces provided.  This approach
      was taken to test the code on Arduino Uno.

   o  MatrixSSL [matrix-ssl]: This library provides a low footprint
      implementation of several cryptographic algorithms including RSA
      and ECC (with a commercial license).  The library in the original
      form takes about 50 kB of ROM and is intended for 32-bit
      platforms.

   This is by no means an exhaustive list, and there exists other
   cryptographic libraries targeting resource-constrained devices.





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   There are also a number of operating systems that are specifically
   targeted for resource-constrained devices.  These operating systems
   may include libraries and code for security.  Hahm et al. [hahmos]
   conducted a survey of such operating systems.  The ARM Mbed OS [mbed]
   is one such operating system that provides various cryptographic
   primitives that are necessary for SSL/TLS protocol implementation as
   well as X509 certificate handling.  The library provides an API for
   developers with a minimal code footprint.  It is intended for various
   ARM platforms such as ARM Cortex M0, ARM Cortex M0+, and ARM Cortex
   M3.

6.  Implementation Experiences

   While evaluating the implementation experiences, we were particularly
   interested in the signature generation operation.  This was because
   our example application discussed in Section 7 required only the
   signature generation operation on the resource-constrained platforms.
   We have summarized the initial results of RSA private-key
   exponentiation performance using AVRCryptoLib [avr-crypto-lib] in
   Table 1.  All results are from a single run since repeating the test
   did not change (or had only minimal impact on) the results.  The
   execution time for a key size of 2048 bits was inordinately long and
   would be a deterrent in real-world deployments.

   +--------------+------------------------+---------------------------+
   | Key length   | Execution time (ms);   | Memory footprint (bytes); |
   | (bits)       | key in RAM             | key in RAM                |
   +--------------+------------------------+---------------------------+
   | 2048         | 1587567                | 1280                      |
   +--------------+------------------------+---------------------------+

              Table 1: RSA Private-Key Operation Performance

   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 the C99 standard and running the Elliptic Curve Digital
   Signature Algorithm (ECDSA) on the Arduino Uno board.  TinyECC
   supports a variety of SEC-2-recommended elliptic curve domain
   parameters [sec2ecc].  The execution time and memory footprint are





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   shown next to each of the curve parameters.  These results were
   obtained by turning on all the optimizations and using assembly code
   where available.

   The results from the performance evaluation of ECDSA in the following
   tables also contain a column stating the approximate comparable RSA
   key length as documented in [sec2ecc].  It is clearly observable that
   for similar security levels, elliptic curve public-key cryptography
   outperforms RSA.

   +-------------+---------------+-----------------+-------------------+
   | 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              |
   +-------------+---------------+-----------------+-------------------+

         Table 2: Performance of ECDSA Sign Operation with TinyECC

   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 is
   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.  However, if 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              |
   +-------------+---------------+-----------------+-------------------+

         Table 3: Performance of ECDSA Sign Operation with TinyECC
                        (No Assembly Optimizations)



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   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 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              |
   +-------------+---------------+-----------------+-------------------+

          Table 4: Performance ECDSA Sign Operation 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.  Arduino Mega has the same 8-bit architecture as
   Arduino Uno, but it has a much larger RAM/ROM.  We used Arduino Mega
   for experimenting with the relic-toolkit.  Again, it is important to
   mention that we used Arduino as it is a convenient prototyping
   platform.  Our intention was to demonstrate the feasibility of the
   entire architecture with public-key cryptography on an 8-bit
   microcontroller.  However, it is important to state that 32-bit
   microcontrollers are much more easily available, at lower costs, and
   are more power efficient.  Therefore, real deployments are better off
   using 32-bit microcontrollers that allow developers to include the
   necessary cryptographic libraries.  There is no good reason to choose
   platforms that do not provide sufficient computing power to run the
   necessary cryptographic operations.

   The relic-toolkit supports Koblitz curves over prime as well as
   binary fields.  We have experimented with Koblitz curves over binary
   fields only.  We do not run our experiments with all the curves
   available in the library since the aim of this work is not to prove
   which curves perform the fastest but rather to show that asymmetric
   cryptography is possible on resource-constrained devices.

   The results from relic-toolkit are documented separately in Tables 5
   and 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



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   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)        |                 |
   +-----------------+--------------+----------------+-----------------+
   | sect163k1       | 261          | 2804           | 1024            |
   | (assembly math) |              |                |                 |
   | sect163k1       | 932          | 2750           | 1024            |
   | sect163r2       | 2243         | 2444           | 1024            |
   | sect233k1       | 1736         | 3675           | 2048            |
   | sect233r1       | 4471         | 3261           | 2048            |
   +-----------------+--------------+----------------+-----------------+

             Table 5: Performance of ECDSA Sign Operation with
                           relic-toolkit (Fast)

   +-----------------+--------------+----------------+-----------------+
   | Curve           | Execution    | Memory         | Comparable RSA  |
   | parameters      | time (ms)    | footprint      | key length      |
   |                 |              | (bytes)        |                 |
   +-----------------+--------------+----------------+-----------------+
   | sect163k1       | 592          | 2087           | 1024            |
   | (assembly math) |              |                |                 |
   | sect163k1       | 2950         | 2215           | 1024            |
   | sect163r2       | 3213         | 2071           | 1024            |
   | sect233k1       | 6450         | 2935           | 2048            |
   | sect233r1       | 6100         | 2737           | 2048            |
   +-----------------+--------------+----------------+-----------------+

      Table 6: Performance of ECDSA Sign Operation with relic-toolkit
                               (Low Memory)















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   It is important to note the following points about the elliptic curve
   measurements:

   o  Some boards (e.g., Arduino Uno) do not provide a hardware random
      number generator.  On such boards, obtaining cryptographic-quality
      randomness is a challenge.  Real-world deployments must rely on a
      hardware random number generator for cryptographic operations such
      as generating a public-private key pair.  The Nordic nRF52832
      board [nordic], for example, provides a hardware random number
      generator.  A detailed discussion on requirements and best
      practices for cryptographic-quality randomness is documented in
      [RFC4086]

   o  For measuring the memory footprint of all the ECC libraries, we
      used the Avrora simulator [avrora].  Only stack memory was used to
      easily track the RAM consumption.

   Tschofenig and Pegourie-Gonnard [armecdsa] have also evaluated the
   performance of ECC on an ARM Coretex platform.  The results for the
   ECDSA sign operation shown in Table 7 are performed on a Freescale
   FRDM-KL25Z board [freescale] that has an ARM Cortex-M0+ 48MHz
   microcontroller with 128 kB of flash memory and 16 kB 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                     |
   +------------------+---------------------+--------------------------+

     Table 7: Performance of ECDSA Sign Operation with an ARM Mbed TLS
                       Stack on Freescale FRDM-KL25Z

   Tschofenig and Pegourie-Gonnard [armecdsa] also measured the
   performance of curves on an ST Nucleo F091 (STM32F091RCT6) board
   [stnucleo] that has an ARM Cortex-M0 48 MHz microcontroller with 256
   kB of flash memory and 32 kB of RAM.  The execution time for the
   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                    |
   +------------------+---------------------+--------------------------+

   Table 8: ECDSA Signature Performance with an ARM Mbed TLS Stack on ST
                        Nucleo F091 (STM32F091RCT6)

   Finally, Tschofenig and Pegourie-Gonnard [armecdsa] also measured the
   RAM consumption by calculating the heap consumed for the
   cryptographic operations using a custom memory allocation handler.
   They did not measure the minimal stack memory consumption.  Depending
   on the curve and the different optimizations enable or disabled, the
   memory consumption for the ECDSA sign operation varied from 1500
   bytes to 15000 bytes.

   At the time of performing these measurements and this study, it was
   unclear which exact elliptic curve(s) would be selected by the IETF
   community for use with resource-constrained devices.  However,
   [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 the signing of data using the curve Ed25519 from the
   NaCl library needs only 23216241 cycles on the same microcontroller
   that we used for our evaluations (Arduino Mega ATmega2560).  This
   corresponds to about 1451 milliseconds of execution time.  When
   compared to the results for other curves and libraries that offer a



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   similar level of security (such as sect233r1 and sect233k1), this
   implementation far outperforms all others.  As such, it is
   recommended that the IETF community use 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                              |
      +------------------------+------------------------------------+

           Table 9: Summary of Library Flash Memory Consumption

   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.  By no means are these
   numbers the final source for measurements, and some curves presented
   here may no longer be acceptable for real in-the-wild deployments.
   For example, Mosdorf et al. [mosdorf] and Liu et al. [tinyecc] also
   document the performance of ECDSA on similar resource-constrained
   devices.

7.  Example Application

   We developed an example application on the Arduino platform to use
   public-key cryptography, data-object security, and an easy
   provisioning model.  Our application was originally developed to test
   different approaches to supporting communications to "always off"
   sensor nodes.  These battery-operated or energy-scavenging nodes do
   not have enough power to stay on at all times.  They wake up
   periodically and transmit their readings.

   Such sensor nodes can be supported in various ways.  [CoAP-SENSORS]
   was an early multicast-based approach.  In the current application,
   we have switched to using resource directories [CoRE-RD] and publish-
   subscribe brokers [CoAP-BROKER] 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 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



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   periodically update the readings.  All queries from the rest of the
   world go to the publish-subscribe broker.

   We constructed a system with four entities:

   Sensor:  This is an Arduino-based device that runs a CoAP publish-
      subscribe broker client and relic-toolkit.  Relic takes 29 kB of
      flash memory, and the simple CoAP client takes roughly 3 kB.

   Publish-Subscribe Broker:  This is a publish-subscribe broker that
      holds resources on the sensor's behalf.  The sensor registers
      itself to this node.

   Resource Directory:  While physically in the same node in our
      implementation, a resource directory is a logical function that
      allows sensors and publish-subscribe brokers to register resources
      in the directory.  These resources can be queried by applications.

   Application:  This is a simple application that runs on a general
      purpose computer and can retrieve both registrations from the
      resource directory and most recent sensor readings from the
      publish-subscribe broker.

   The security of this system relies on a secure-shell-like approach.
   In Step 1, upon first boot, sensors generate keys and register
   themselves in the publish-subscribe broker.  Their public key is
   submitted along with the registration as an attribute in the CoRE
   Link Format data [RFC6690].

   In Step 2, when the sensor makes a measurement, it sends an update to
   the publish-subscribe broker and signs the message contents with a
   JSON Object Signing and Encryption (JOSE) signature on the used JSON
   [RFC7515] and Sensor Measurement List (SenML) payload [MT-SenML].
   The sensor can also alternatively use CBOR Object Signing and
   Encryption (COSE) [RFC8152] for signing the sensor measurement.

   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.





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   To verify the feasibility of our architecture, we developed a
   proof-of-concept prototype.  In our prototype, the sensor was
   implemented using the Arduino Ethernet shield over an Arduino Mega
   board.  Our implementation uses the standard C99 programming language
   on the Arduino Mega board.  In this prototype, the publish-subscribe
   broker and the Resource Directory (RD) reside on the same physical
   host.  A 64-bit x86 Linux machine serves as the broker and the RD,
   while a similar but physically distinct 64-bit x86 Linux machine
   serves as the client that requests data from the sensor.  We chose
   the Relic library version 0.3.1 for our sample prototype as it can be
   easily compiled for different bit-length processors.  Therefore, we
   were able to use it on the 8-bit processor of the Arduino Mega, as
   well as on the 64-bit processor of the x86 client.  We used ECDSA to
   sign and verify data updates with the standard sect163k1 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 Representational State
   Transfer (REST) interfaces.  We also developed a minimalistic CoAP
   C-library for the Arduino sensor and for the client requesting data
   updates for a resource.  The library has small RAM requirements and
   uses stack-based allocation only.  It is interoperable with the Java
   implementation of CoAP running on the gateway.  The location of the
   resource directory was configured into the smart object sensor by
   hardcoding the IP address.  A real implementation based on this
   prototype would instead use the domain name system for obtaining the
   location of the resource directory.

   Our intention was to demonstrate that it is possible to implement the
   entire architecture with public-key cryptography on an 8-bit
   microcontroller.  The stated values can be improved further by a
   considerable amount.  For example, the flash memory and RAM
   consumption is relatively high because some of the Arduino libraries
   were used out of the box, and there are several functions that 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
   modern development boards have a 32-bit microcontroller since they
   are more economical and have better energy efficiency.









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8.  Design Trade-Offs

   This section attempts to make some early conclusions regarding trade-
   offs in the design space, based on deployment considerations for
   various mechanisms and the relative ease or difficulty of
   implementing them.  In particular, this analysis looks at layering,
   freshness, and the choice of symmetric vs. asymmetric cryptography.

8.1.  Feasibility

   The first question is whether using cryptographic security and
   asymmetric cryptography in particular is feasible at all on resource-
   constrained devices.  The numbers above give a mixed message.
   Clearly, an implementation of a significant cryptographic operation
   such as public-key signing can be done in a surprisingly small amount
   of code space.  It could even be argued that our chosen prototype
   platform was unnecessarily restrictive in the amount of code space it
   allows: we chose this platform on purpose to demonstrate something
   that is as resource constrained and difficult as possible.

   A recent trend in microcontrollers is the introduction of 32-bit CPUs
   that are becoming cheaper and more easily available than 8-bit CPUs,
   in addition to being more easily programmable.  The flash memory size
   is probably easier to grow than other parameters in microcontrollers.
   Flash memory size is not expected to be the most significant limiting
   factor.  Before picking a platform, developers should also plan for
   firmware updates.  This would essentially mean that the platform
   should at least have a flash memory size of the total code size * 2,
   plus some space for buffer.

   The situation is less clear with regards to the amount of CPU power
   needed to run the algorithms.  The demonstrated speeds are sufficient
   for many applications.  For instance, a sensor that wakes up every
   now and then can likely spend a fraction of a second, or even spend
   multiple seconds in some cases, for the computation of a signature
   for the message that it is about to send.  Most applications that use
   protocols such as DTLS that use public-key cryptography only at the
   beginning of the session would also be fine with any of these
   execution times.

   Yet, with reasonably long key sizes, the execution times are in the
   seconds, dozens of seconds, or even longer.  For some applications,
   this is too long.  Nevertheless, these algorithms can successfully be
   employed in resource-constrained devices for the following reasons:

   o  With the right selection of algorithms and libraries, the
      execution times can actually be very small (less than 500 ms).




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   o  As discussed in [wiman], in general, the power requirements
      necessary to turn the radio on/off and sending or receiving
      messages are far bigger than those needed to execute cryptographic
      operations.  While there are newer radios that significantly lower
      the energy consumption of sending and receiving messages, there is
      no good reason to choose platforms that do not provide sufficient
      computing power to run the necessary cryptographic operations.

   o  Commercial libraries and the use of full potential for various
      optimizations will provide a better result than what we arrived at
      in this memo.

   o  Using public-key cryptography only at the beginning of a session
      will reduce the per-packet processing times significantly.

   While we did not do an exhaustive performance evaluation of
   asymmetric key-pair generation on resource-constrained devices, we
   did note that it is possible for such devices to generate a new key
   pair.  Given that this operation would only occur in rare
   circumstances (such as a factory reset or ownership change) and its
   potential privacy benefits, developers should provide mechanisms for
   generating new identities.  However, it is extremely important to
   note that the security of this operation relies on access to
   cryptographic-quality randomness.

8.2.  Freshness

   In our architecture, if implemented as described thus far, messages
   along with their signatures sent from the sensors to the publish-
   subscribe broker can be recorded and replayed by an eavesdropper.
   The publish-subscribe broker has no mechanism to distinguish
   previously received packets from those that are retransmitted by the
   sender or replayed by an eavesdropper.  Therefore, it is essential
   for the smart objects to ensure that data updates include a freshness
   indicator.  However, ensuring freshness on constrained devices can be
   non-trivial because of several reasons, which include:

   o  Communication is mostly unidirectional to save energy.

   o  Internal clocks might not be accurate and may be reset several
      times during the operational phase of the smart object.

   o  Network time synchronization protocols such as the Network Time
      Protocol (NTP) [RFC5905] are resource intensive and therefore may
      be undesirable in many smart object networks.






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   There are several different methods that can be used in our
   architecture for replay protection.  The selection of the appropriate
   choice depends on the actual deployment scenario.

   Including sequence numbers in signed messages can provide an
   effective method of replay protection.  The publish-subscribe broker
   should verify the sequence number of each incoming message and accept
   it only if it is greater than the highest previously seen sequence
   number.  The publish-subscribe broker drops any packet with a
   sequence number that has already been received or if the received
   sequence number is greater than the highest previously seen sequence
   number by an amount larger than the preset threshold.

   Sequence numbers can wrap around at their maximum value; 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
   resynchronize with the publish-subscribe broker if a reset message is
   received.  The sensors resynchronize 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 that include
   timestamps to allow the publish-subscribe broker to determine the
   time when the update was created.  For example, when the publish-



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   subscribe broker is collecting temperature data, it may be necessary
   to know when exactly the temperature measurement was made by the
   sensor.  A simple solution to this problem is for the publish-
   subscribe broker to assume that the data object was created when it
   receives the update.  In a relatively reliable network with low RTT,
   it can be acceptable to make such an assumption.  However, most
   networks are susceptible to packet loss and hostile attacks making
   this assumption unsustainable.

   Depending on the hardware used by the smart objects, they may have
   access to accurate hardware clocks, which can be used to include
   timestamps in the signed updates.  These timestamps are included in
   addition to sequence numbers.  The clock time in the smart objects
   can be set by the manufacturer, or the current time can be
   communicated by the publish-subscribe broker during the registration
   phase.  However, these approaches require the smart objects to either
   rely on the long-term accuracy of the clock set by the manufacturer
   or 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 coordinate their sleep
   cycles, or if the publish-subscribe broker computes an average or
   mean of updates collected from multiple smart objects, it is
   important for the network nodes to synchronize the time among them.
   This can be done by using existing synchronization schemes.

8.3.  Layering

   It would be useful to select just one layer where security is
   provided at.  Otherwise, a simple device needs to implement multiple
   security mechanisms.  While some code can probably be shared across
   such implementations (like algorithms), it is likely that most of the
   code involving the actual protocol machinery cannot.  Looking at the
   different layers, here are the choices and their implications:

   link layer:  This is probably the most common solution today.  The
      primary 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 smart home weighing
      scale, for instance, can support WLAN security, but without some



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      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 the link layer, network layer, and in some cases, transport
      layer, cannot be protected against.  However, if the upper layers
      have been protected, such attacks can at most result in a denial
      of service.  Since denial of service can often be caused anyway,
      it is not clear if this is a real drawback.

   data-object layer:  This solution does not protect any of the
      protocol layers but protects individual data elements being sent.
      It works particularly well when there are multiple application-
      layer entities on the path of the data.  Smart object networks are
      likely to employ such entities for storage, filtering, aggregation
      and other reasons, and as such, an end-to-end solution is the only
      one that can protect the actual data.




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      The downside is that the lower layers are not protected.  But
      again, as long as the data is protected and checked upon every
      time it passes through an application-level entity, it is not
      clear that there are attacks beyond denial of service.

      The main question mark is whether this type of a solution provides
      sufficient advantages over the more commonly implemented transport
      and application-layer solutions.

8.4.  Symmetric vs. Asymmetric Crypto

   The second trade-off that is worth discussing is the use of plain
   asymmetric cryptographic mechanisms, plain symmetric cryptographic
   mechanisms, or some mixture thereof.

   Contrary to popular cryptographic community beliefs, a symmetric
   cryptographic solution can be deployed in large scale.  In fact, one
   of the largest deployments of cryptographic security, the cellular
   network authentication system, uses Subscriber Identification Module
   (SIM) cards that are based on symmetric secrets.  In contrast,
   public-key systems have yet to show an 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 Section 6, the time needed to calculate some of
   the asymmetric cryptographic operations with reasonable key lengths
   can be significant.  There are two contrary observations that can be
   made from this.  First, recent wisdom indicates that computing power
   on resource-constrained devices is far cheaper than transmission
   power [wiman], and it 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 it works less
   well for data-object security, particularly when the number of
   communicating entities is not exactly two.











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9.  Summary

   This document makes several security recommendations based on our
   implementation experience.  We summarize some of the important ones
   here:

   o  Developers and product designers should choose the hardware after
      determining the security requirements for their application
      scenario.

   o  ECC outperforms RSA-based operations; therefore, it is recommended
      for resource-constrained devices.

   o  Cryptographic-quality randomness is needed for many security
      protocols.  Developers and vendors should ensure that the
      sufficient randomness is available for security critical tasks.

   o  32-bit microcontrollers are much more easily available, at lower
      costs, and are more power efficient.  Therefore, real-world
      deployments are better off using 32-bit microcontrollers.

   o  Developers should provide mechanisms for devices to generate new
      identities at appropriate times during their life cycle, for
      example, after a factory reset or an ownership handover.

   o  Planning for firmware updates is important.  The hardware platform
      chosen should at least have a flash memory size of the total code
      size * 2, plus some space for buffer.

10.  Security Considerations

   This entire memo deals with security issues.

11.  IANA Considerations

   This document has no IANA actions.

12.  Informative References

   [arduino-uno]
              Arduino, "Arduino Uno REV3",
              <http://arduino.cc/en/Main/arduinoBoardUno>.

   [armecdsa] Tschofenig, H. and M. Pegourie-Gonnard, "Performance
              Investigations", March 2015,
              <https://www.ietf.org/proceedings/92/slides/
              slides-92-lwig-3.pdf>.




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   [avr-crypto-lib]
              Das Labor, "AVR-Crypto-Lib", February 2014,
              <http://www.das-labor.org/wiki/AVR-Crypto-Lib/en>.

   [avr-cryptolib]
              "AVRCryptoLib", <http://www.emsign.nl/>.

   [avrora]   Avora, "The AVR Simulation and Analysis Framework",
              <http://compilers.cs.ucla.edu/avrora/>.

   [CoAP-BROKER]
              Koster, M., Keranen, A., and J. Jimenez, "Publish-
              Subscribe Broker for the Constrained Application Protocol
              (CoAP)", Work in Progress, draft-ietf-core-coap-pubsub-04,
              March 2018.

   [CoAP-SECURITY]
              Arkko, J. and A. Keranen, "CoAP Security Architecture",
              Work n Progress, draft-arkko-core-security-arch-00, July
              2011.

   [CoAP-SENSORS]
              Arkko, J., Rissanen, H., Loreto, S., Turanyi, Z., and O.
              Novo, "Implementing Tiny COAP Sensors", Wok in Progress,
              draft-arkko-core-sleepy-sensors-01, July 2011.

   [CoRE-RD]  Shelby, Z., Koster, M., Bormann, C., Stok, P., and C.
              Amsuess, "CoRE Resource Directory", Work in Progress,
              draft-ietf-core-resource-directory-13, March 2018.

   [freescale]
              ARM Mbed, "FRDM-KL25Z",
              <https://developer.mbed.org/platforms/KL25Z/>.

   [hahmos]   Hahm, O., Baccelli, E., Petersen, H., and N. Tsiftes,
              "Operating systems for low-end devices in the internet of
              things: a survey", IEEE Internet of Things Journal,
              Vol. 3, Issue 5, DOI 10.1109/JIOT.2015.2505901, October
              2016.

   [HIP-DEX]  Moskowitz, R., Ed. and R. Hummen, "HIP Diet EXchange
              (DEX)", Work in Progress, draft-ietf-hip-dex-06, December
              2017.

   [huang]    Huang, C., "LOFT: Low-overhead freshness transmission in
              sensor networks", IEEE, DOI 10.1109/SUTC.2008.38, June
              2008.




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   [IoT-BOOTSTRAPPING]
              Sarikaya, B., Sethi, M., and A. Sangi, "Secure IoT
              Bootstrapping: A Survey", Work in Progress,
              draft-sarikaya-t2trg-sbootstrapping-03, February 2017.

   [IoT-SECURITY]
              Garcia-Morchon, O., Kumar, S., and M. Sethi,
              "State-of-the-Art and Challenges for the Internet of
              Things Security", Work in Progress,
              draft-irtf-t2trg-iot-seccons-14, April 2018.

   [IPV6-LOWPAN-SEC]
              Park, S., Kim, K., Haddad, W., Chakrabarti, S., and J.
              Laganier, "IPv6 over Low Power WPAN Security Analysis",
              Work in Progress, draft-daniel-6lowpan-security-
              analysis-05, March 2011.

   [matrix-ssl]
              Inside Secure, "GUARD TLS Toolkit (formerly Matrix SSL)",
              <http://www.matrixssl.org/>.

   [mbed]     ARM Mbed, "Mbed TLS",
              <https://www.mbed.com/en/technologies/security/mbed-tls/>.

   [micronacl]
              MicroNaCl, "The Networking and Cryptography library for
              microcontrollers", <http://munacl.cryptojedi.org/>.

   [mosdorf]  Mosdorf, M. and W. Zabolotny, "Implementation of elliptic
              curve cryptography for 8-bit and 32-bit embedded systems -
              time efficiency and power consumption analysis", Pomiary
              Automatyka  Kontrola, 2010.

   [MT-SenML] Jennings, C., Shelby, Z., Arkko, J., Keranen, A., and C.
              Bormann, "Sensor Measurement Lists (SenML)", Work in
              Progress, draft-ietf-core-senml-15, May 2018.

   [nacl]     NaCl, "Networking and Cryptography library",
              <http://nacl.cr.yp.to/>.

   [naclavr]  Hutter, M. and P. Schwabe, "NaCl on 8-Bit AVR
              Microcontrollers", International Conference on
              Cryptology in Africa, Computer Science, Vol. 7918, pp.
              156-172, February 2013,
              <https://doi.org/10.1007/978-3-642-38553-7_9>.






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   [nesC]     Gay, D., Levis, P., von Behren, R., Welsh, M., Brewer, E.,
              and D. Culler, "The nesC language: A holistic approach to
              networked embedded systems", ACM SIGPLAN Notices, Vol. 38,
              Issue 5, DOI 10.1145/781131.781133, 2003.

   [nordic]   Nordic Semiconductor, "nRF52832 Product Specification
              v1.3", March 2017, <http://infocenter.nordicsemi.com/pdf/
              nRF52832_PS_v1.3.pdf>.

   [relic-toolkit]
              "relic", March 2017,
              <https://github.com/relic-toolkit/relic>.

   [RFC3748]  Aboba, B., Blunk, L., Vollbrecht, J., Carlson, J., and H.
              Levkowetz, Ed., "Extensible Authentication Protocol
              (EAP)", RFC 3748, DOI 10.17487/RFC3748, June 2004,
              <https://www.rfc-editor.org/info/rfc3748>.

   [RFC3972]  Aura, T., "Cryptographically Generated Addresses (CGA)",
              RFC 3972, DOI 10.17487/RFC3972, March 2005,
              <https://www.rfc-editor.org/info/rfc3972>.

   [RFC4086]  Eastlake 3rd, D., Schiller, J., and S. Crocker,
              "Randomness Requirements for Security", BCP 106, RFC 4086,
              DOI 10.17487/RFC4086, June 2005,
              <https://www.rfc-editor.org/info/rfc4086>.

   [RFC4303]  Kent, S., "IP Encapsulating Security Payload (ESP)",
              RFC 4303, DOI 10.17487/RFC4303, December 2005,
              <https://www.rfc-editor.org/info/rfc4303>.

   [RFC5191]  Forsberg, D., Ohba, Y., Ed., Patil, B., Tschofenig, H.,
              and A. Yegin, "Protocol for Carrying Authentication for
              Network Access (PANA)", RFC 5191, DOI 10.17487/RFC5191,
              May 2008, <https://www.rfc-editor.org/info/rfc5191>.

   [RFC5246]  Dierks, T. and E. Rescorla, "The Transport Layer Security
              (TLS) Protocol Version 1.2", RFC 5246,
              DOI 10.17487/RFC5246, August 2008,
              <https://www.rfc-editor.org/info/rfc5246>.

   [RFC5406]  Bellovin, S., "Guidelines for Specifying the Use of IPsec
              Version 2", BCP 146, RFC 5406, DOI 10.17487/RFC5406,
              February 2009, <https://www.rfc-editor.org/info/rfc5406>.







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   [RFC5905]  Mills, D., Martin, J., Ed., Burbank, J., and W. Kasch,
              "Network Time Protocol Version 4: Protocol and Algorithms
              Specification", RFC 5905, DOI 10.17487/RFC5905, June 2010,
              <https://www.rfc-editor.org/info/rfc5905>.

   [RFC6078]  Camarillo, G. and J. Melen, "Host Identity Protocol (HIP)
              Immediate Carriage and Conveyance of Upper-Layer Protocol
              Signaling (HICCUPS)", RFC 6078, DOI 10.17487/RFC6078,
              January 2011, <https://www.rfc-editor.org/info/rfc6078>.

   [RFC6347]  Rescorla, E. and N. Modadugu, "Datagram Transport Layer
              Security Version 1.2", RFC 6347, DOI 10.17487/RFC6347,
              January 2012, <https://www.rfc-editor.org/info/rfc6347>.

   [RFC6574]  Tschofenig, H. and J. Arkko, "Report from the Smart Object
              Workshop", RFC 6574, DOI 10.17487/RFC6574, April 2012,
              <https://www.rfc-editor.org/info/rfc6574>.

   [RFC6690]  Shelby, Z., "Constrained RESTful Environments (CoRE) Link
              Format", RFC 6690, DOI 10.17487/RFC6690, August 2012,
              <https://www.rfc-editor.org/info/rfc6690>.

   [RFC7230]  Fielding, R., Ed. and J. Reschke, Ed., "Hypertext Transfer
              Protocol (HTTP/1.1): Message Syntax and Routing",
              RFC 7230, DOI 10.17487/RFC7230, June 2014,
              <https://www.rfc-editor.org/info/rfc7230>.

   [RFC7252]  Shelby, Z., Hartke, K., and C. Bormann, "The Constrained
              Application Protocol (CoAP)", RFC 7252,
              DOI 10.17487/RFC7252, June 2014,
              <https://www.rfc-editor.org/info/rfc7252>.

   [RFC7296]  Kaufman, C., Hoffman, P., Nir, Y., Eronen, P., and T.
              Kivinen, "Internet Key Exchange Protocol Version 2
              (IKEv2)", STD 79, RFC 7296, DOI 10.17487/RFC7296, October
              2014, <https://www.rfc-editor.org/info/rfc7296>.

   [RFC7401]  Moskowitz, R., Ed., Heer, T., Jokela, P., and T.
              Henderson, "Host Identity Protocol Version 2 (HIPv2)",
              RFC 7401, DOI 10.17487/RFC7401, April 2015,
              <https://www.rfc-editor.org/info/rfc7401>.

   [RFC7515]  Jones, M., Bradley, J., and N. Sakimura, "JSON Web
              Signature (JWS)", RFC 7515, DOI 10.17487/RFC7515, May
              2015, <https://www.rfc-editor.org/info/rfc7515>.






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   [RFC7748]  Langley, A., Hamburg, M., and S. Turner, "Elliptic Curves
              for Security", RFC 7748, DOI 10.17487/RFC7748, January
              2016, <https://www.rfc-editor.org/info/rfc7748>.

   [RFC7815]  Kivinen, T., "Minimal Internet Key Exchange Version 2
              (IKEv2) Initiator Implementation", RFC 7815,
              DOI 10.17487/RFC7815, March 2016,
              <https://www.rfc-editor.org/info/rfc7815>.

   [RFC8032]  Josefsson, S. and I. Liusvaara, "Edwards-Curve Digital
              Signature Algorithm (EdDSA)", RFC 8032,
              DOI 10.17487/RFC8032, January 2017,
              <https://www.rfc-editor.org/info/rfc8032>.

   [RFC8152]  Schaad, J., "CBOR Object Signing and Encryption (COSE)",
              RFC 8152, DOI 10.17487/RFC8152, July 2017,
              <https://www.rfc-editor.org/info/rfc8152>.

   [rsa-8bit] Gura, N., Patel, A., Wander, A., Eberle, H., and S.
              Shantz, "Comparing Elliptic Curve Cryptography and RSA on
              8-bit CPUs", DOI 10.1007/978-3-540-28632-5_9, 2004.

   [rsa-high-speed]
              Koc, C., "High-Speed RSA Implementation", November 1994,
              <http://storage.jak-stik.ac.id/rsasecurity/tr201.pdf>.

   [sec2ecc]  Certicom Research, "SEC 2: Recommended Elliptic Curve
              Domain Parameters", Version 2.0, January 2010.

   [stnucleo] STMicroelectronics, "NUCLEO-F091RC",
              <http://www.st.com/en/evaluation-tools/
              nucleo-f091rc.html/>.

   [tinyecc]  Liu, A. and P. Nig, "TinyECC: A Configurable Library for
              Elliptic Curve Cryptography in Wireless Sensor Networks
              (Version 2.0)", NCSU College of Engineering, February
              2011, <http://discovery.csc.ncsu.edu/software/TinyECC/>.

   [wiman]    Margi, C., Oliveira, B., Sousa, G., Simplicio, M., Paulo,
              S., Carvalho, T., Naslund, M., and R. Gold, "Impact of
              Operating Systems on Wireless Sensor Networks (Security)
              Applications and Testbeds", Proceedings of the 19th
              International Conference on Computer Communciations and
              Networks, DOI 10.1109/ICCCN.2010.5560028, 2010.

   [wiselib]  "wiselib", February 2015,
              <https://github.com/ibr-alg/wiselib>.




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Acknowledgments

   The authors would like to thank Mats Naslund, Salvatore Loreto, Bob
   Moskowitz, Oscar Novo, Vlasios Tsiatsis, Daoyuan Li, Muhammad Waqas,
   Eric Rescorla, and Tero Kivinen for interesting discussions in this
   problem space.  The authors would also like to thank Diego Aranha for
   helping with the relic-toolkit configurations and Tobias Baumgartner
   for helping with questions regarding wiselib.

   Tim Chown, Samita Chakrabarti, Christian Huitema, Dan Romascanu, Eric
   Vyncke, and Emmanuel Baccelli provided valuable comments that helped
   us improve this document.

Authors' Addresses

   Mohit Sethi
   Ericsson
   Jorvas  02420
   Finland

   Email: mohit@piuha.net


   Jari Arkko
   Ericsson
   Jorvas  02420
   Finland

   Email: jari.arkko@piuha.net


   Ari Keranen
   Ericsson
   Jorvas  02420
   Finland

   Email: ari.keranen@ericsson.com


   Heidi-Maria Back
   Nokia
   Helsinki  00181
   Finland

   Email: heidi.back@nokia.com






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