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Triathlon of lightweight block ciphers for the Internet of things


In this paper, we introduce a framework for the benchmarking of lightweight block ciphers on a multitude of embedded platforms. Our framework is able to evaluate the execution time, RAM footprint, as well as binary code size, and allows one to define a custom “figure of merit” according to which all evaluated candidates can be ranked. We used the framework to benchmark implementations of 19 lightweight ciphers, namely AES, Chaskey, Fantomas, HIGHT, LBlock, LEA, LED, Piccolo, PRESENT, PRIDE, PRINCE, RC5, RECTANGLE, RoadRunneR, Robin, Simon, SPARX, Speck, and TWINE, on three microcontroller platforms: 8-bit AVR, 16-bit MSP430, and 32-bit ARM. Our results bring some new insights into the question of how well these lightweight ciphers are suited to secure the Internet of things. The benchmarking framework provides cipher designers with an easy-to-use tool to compare new algorithms with the state of the art and allows standardization organizations to conduct a fair and consistent evaluation of a large number of candidates.

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  1. 1.

    The main reason for evaluating the execution time for ARM on a development board is that we could not find a cycle-accurate Cortex-M instruction set simulator of good quality that is freely available.

  2. 2.

    The maintainers of the BLOC project merged our pull request on GitHub that fixed the mentioned issues, see

  3. 3.

    All results reported in this paper are based on version 1.1.20 of the FELICS framework, which can be downloaded from

  4. 4.

    One can get a rough estimate of the energy consumption by simply forming the product of execution time, average power consumption of the target processor, and supply voltage. More accurate energy figures could be obtained by extending the framework to support power measurements on microprocessor development boards.


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We thank all contributors listed at for the submitted implementations and their support for a fair evaluation of lightweight block ciphers. Daniel Dinu and Léo Perrin were supported by the CORE project ACRYPT (ID C12-15-4009992), funded by the Fonds National de la Recherche (FNR) Luxembourg.

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Correspondence to Johann Großschädl.


Target devices

8-bit AVR ATmega128 microcontroller

The ATmega128 [4] microcontroller developed by Atmel is based on an 8-bit RISC architecture and provides 133 instructions, which are encoded to be either 16 or 32 bits wide. Most of the instructions are executed in only one or two clock cycles. The ATmega128 features a two-stage pipeline, making it possible to execute an instruction while the next instruction is fetched from program memory. In addition, it comes with a relatively large register file consisting of 32 general-purpose registers (R0 to R31) of 8-bit width. Six registers can be used as three 16-bit pointers (X, Y, and Z) to access the data space. All 32 registers are directly connected to the arithmetic logic unit (ALU). The standard ALU instructions have a two-address format, which allows them to read two 8-bit operand words from two independent registers and write the result of the operation back to one of them. Like other members of the 8-bit AVR family, the ATmega128 uses a Harvard architecture (i.e., separate memories, buses, and address spaces for program and data) to maximize performance and parallelism. The memory sub-system includes 128 kB of flash (for storing program code), 4 kB of SRAM, and 4 kB of EEPROM.

16-bit MSP430F1611 microcontroller

The MSP430F1611 [53] is a 16-bit microcontroller from Texas Instruments that contains a RISC CPU optimized for ultra-low power consumption and various peripheral modules. A distinguishing feature of the MSP430 architecture is its minimalist instruction set comprising only 27 core instructions and 24 emulated instructions. The length of an instruction can vary between one and three 16-bit words, i.e., between two and six bytes. Depending on the instruction format, the 27 core instructions fall into three categories: double-operand instructions (which overwrite one of the two operands with the result), single-operand instructions, and jumps. The MSP430 instruction set is highly orthogonal and supports seven addressing modes for the source operand and four addressing modes for the destination operand. Depending on the used addressing modes, double-operand instructions have a latency of between one clock cycle (when source and destination operands are held in registers) and six clock cycles (operands are in RAM or flash). There are 16 registers, of which four, namely R0 to R3, serve a special purpose. The von Neumann memory system of the MSP430F1611 consists of 10 kB RAM and 48 kB flash.

32-bit ARM Cortex-M3 microcontroller

The Cortex-M3 is a member of the ARM Cortex-M series of 32-bit microcontrollers that was specifically designed to achieve high system performance in power- and cost-sensitive embedded applications [3]. It is based on the ARMv7-M architecture and supports Thumb-2 technology, which extends the 16-bit fixed-width Thumb instruction set with some additional 32-bit ARM instructions, whereby 16-bit and 32-bit instructions can be freely intermixed. Data processing instructions have a conventional three-address format that allows the target register to be distinct from the two source operands. The first operand must always be one of the 13 general-purpose 32-bit registers, while the second operand can be a register, an immediate value, or a register with an optional shift. Many instructions can be executed conditionally, based on condition flags set by another instruction. Cortex-M3 microcontrollers incorporate a Harvard architecture (enabling simultaneous instruction fetch with data load/store) and have a three-stage pipeline with branch speculation. The specific Cortex-M3 device we use for benchmarking is an Arduino Due board equipped with an Atmel SAM3X8 that features 512 kB flash and 96 kB RAM.

API and implementation requirements

To unify evaluation conditions, our framework imposes some requirements on the implementation of a block cipher. Firstly, basic operations must be performed by functions having the following C prototypes.

void RunEncryptionKeySchedule(uint8_t *key, uint8_t *roundKeys);

void Encrypt(uint8_t *block, uint8_t


void RunDecryptionKeySchedule(uint8_t *key, uint8_t *roundKeys);

void Decrypt(uint8_t *block, uint8_t *roundKeys);

Each of the above functions should be implemented in its own C file. If the cipher key schedule is the same for encryption and decryption then only the encryption key schedule function has to be implemented. The framework takes a common key schedule into account when computing the different metrics. Secondly, all other common code sections should be placed in separate functions to reduce the overall code size. The implementer needs to add the names of the common files to the implementation info file, which gets parsed by the framework when extracting the three metrics for the implementation. Thirdly, the implementer has to choose whether the constants used by the cipher should be stored in flash/ROM or RAM. However, this flexibility comes at the expense that the implementer has to define and use a dedicated macro to read the constant value(s). Fourthly, the block size used by the implementation must be a multiple of 64 bits.

While these requirements guarantee the same evaluation conditions for an accurate assessment of the performance of a block cipher in various different evaluation scenarios, they limit the applicability of some optimization techniques like bit-slicing. Even though bit-sliced implementations can be very fast, they have the disadvantage of high memory consumption and can only be used in non-feedback modes of operation (e.g., CTR mode). However, the performance of a cipher implementation in such (highly) specific settings does not say anything about the cipher’s performance in more general usage scenarios, which is what we are mainly interested in and our framework was designed for. The benchmarking toolsuite is able to verify the compliance with the formulated requirements and to check the correctness of an implementation with the help of test vectors. Since the metrics extraction process is completely automated, the toolsuite is easy to use, even for beginners with little experience.

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Dinu, D., Corre, Y.L., Khovratovich, D. et al. Triathlon of lightweight block ciphers for the Internet of things. J Cryptogr Eng 9, 283–302 (2019).

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  • IoT
  • Lightweight cryptography
  • Block ciphers
  • Evaluation framework
  • Benchmarking