Crypto-Resistant Methods and Random Number Generators in Internet of Things (Iot) Devices

Abstract

Subject of research: crypto-resistant methods and tools of generating random sequences and hardware support of cryptographic transformations in IoT devices. The aim of the article is to study crypto-resistant methods and tools for generating and testing random sequences suitable for use in IoT devices with limited resources; determination of circuit implementations of random sequences hardware generators; formation of conclusions on the use of random number generators (RNG) in cryptographic protection systems of the IoT network. The article solves the following tasks: analysis of methods and hardware for generating random sequences to protect IoT solutions with limited resources; identification of safe and effective technologies for the implementation of RNG; classification of RNG attacks; analysis of the shortcomings of the practical use of statistical test packages to assess the quality of random sequences of RNG; evaluation of the speed of cryptoaccelerators of hardware support for cryptographic transformations; providing practical guidance on RNG for use in resource-constrained IoT devices. Research methods: method of structural and functional analysis of RNG and IoT devices, cryptographic methods of information protection, methods of random sequence generation, method of stability analysis of systems, methods of construction of autonomous Boolean networks and Boolean chaos analysis, methods of quality assessment of random sequences. Results of work: the analysis of technologies and circuit decisions of hardware RNG on characteristics: quality of numbers’ randomness and unpredictability of sequences, speed, power consumption, miniaturization, possibility of integral execution; providing practical recommendations for the use of RNG in cryptographic protection systems of the IoT network. The novelty of the study is the analysis of methods and hardware to support technologies for generating random sequences in the system of cryptographic protection of IoT solutions; classification of attacks on RNG and features of protection against them; identification of effective RNG technologies and circuit solutions for use in low-power IoT devices with limited computing resources; providing practical recommendations for the use of RNG in cryptographic protection systems of the IoT network. The analysis of technologies and circuit solutions allowed to draw the following conclusions: protection of IoT solutions includes: security of IoT network nodes and their connection to the cloud using secure protocols, ensuring confidentiality, authenticity and integrity of IoT data by cryptographic methods, attack analysis and network cryptographic stability; the initial basis for the protection of IoT solutions is the true randomness of the formed RNG sequences and used in algorithms for cryptographic transformation of information to protect it; feature of IoT devices is their heterogeneity and geographical distribution, limited computing resources and power supply, small size; The most effective (reduce power consumption and increase the generation rate) for use in IoT devices are RNG exclusively on a digital basis, which implements a three-stage process: the initial digital circuit, normalizer and random number flow generator; Autonomous Boolean networks (ABN) allow to create RNG with unique characteristics: the received numbers are really random, high speed – the number can be received in one measure, the minimum power consumption, miniature, high (up to 3 GHz) throughput of Boolean chaos; a promising area of ABN development is the use of optical logic valves for the construction of optical ABN with a bandwidth of up to 14 GHz; the classification of known classes of RNG attacks includes: direct cryptanalytic attacks, attacks based on input data, attacks based on the disclosure of the internal state of RNG, correlation attacks and special attacks; statistical test packages to evaluate RNG sequences have some limitations or shortcomings and do not replace cryptanalysis; Comparison of cryptoaccelerators with cryptographic transformation software shows their significant advantages: for AES block encryption algorithm, speeds increase by 10-20 times in 8/16-bit cryptoaccelerators and 150 times in 32-bit, growth hashing of SHA-256 in 32-bit cryptoaccelerators more than 100 times, and for the NMAS algorithm - up to 500 times.