RFC 8387
Practical Considerations and Implementation Experiences in Securing Smart Object Networks
Pages: 33
Informational
Informational
Part 1 of 2 – Pages 1 to 18
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 NetworksAbstract
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.
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
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
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,
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.
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
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.
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
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
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.
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.
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
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)
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
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)
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.
+------------------+---------------------+--------------------------+ | 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
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.
(page 18 continued on part 2)