Request for Comments: 8387
Practical Considerations and Implementation Experiences in
Securing Smart Object Networks
This memo describes challenges associated with securing resource- constrained smart object devices. The memo describes a possible deployment model 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.
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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
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.
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:
- 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.
- Manual configuration is rarely, if at all, possible, as the necessary skills are missing in typical installation environments (such as in family homes).
- 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.
- 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.
- 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.
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:
- Ability for intermediaries to act as caches to support different sleep schedules, without the security model being impacted.
- 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.
- 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.
- 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
+-----------------+--------------+----------------+-----------------+ | 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
It is important to note the following points about the elliptic curve measurements:
- 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]
- 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.
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 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.
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.
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.
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:
- With the right selection of algorithms and libraries, the execution times can actually be very small (less than 500 ms).
- 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.
- Commercial libraries and the use of full potential for various optimizations will provide a better result than what we arrived at in this memo.
- 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.
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:
- Communication is mostly unidirectional to save energy.
- Internal clocks might not be accurate and may be reset several times during the operational phase of the smart object.
- 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.
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- 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.
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 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.
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.
This document makes several security recommendations based on our implementation experience. We summarize some of the important ones here:
- Developers and product designers should choose the hardware after determining the security requirements for their application scenario.
- ECC outperforms RSA-based operations; therefore, it is recommended for resource-constrained devices.
- Cryptographic-quality randomness is needed for many security protocols. Developers and vendors should ensure that the sufficient randomness is available for security critical tasks.
- 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.
- 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.
- 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, "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>.
Das Labor, "AVR-Crypto-Lib", February 2014, <http://www.das-labor.org/wiki/AVR-Crypto-Lib/en>.
[avrora] Avora, "The AVR Simulation and Analysis Framework", <http://compilers.cs.ucla.edu/avrora/>.
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.
Arkko, J. and A. Keranen, "CoAP Security Architecture", Work n Progress, draft-arkko-core-security-arch-00, July 2011.
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.
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.
Sarikaya, B., Sethi, M., and A. Sangi, "Secure IoT Bootstrapping: A Survey", Work in Progress, draft-sarikaya-t2trg-sbootstrapping-03, February 2017.
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.
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.
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, "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>. [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", 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>. [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>. [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.
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>.
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.
Mohit Sethi Ericsson Jorvas 02420 Finland
firstname.lastname@example.org Jari Arkko Ericsson Jorvas 02420 Finland Email: email@example.com Ari Keranen Ericsson Jorvas 02420 Finland Email: firstname.lastname@example.org Heidi-Maria Back Nokia Helsinki 00181 Finland Email: email@example.com