A resource efficient pseudo random number generator based on sawtooth maps for Internet of Things

IF 1.5 Q3 COMPUTER SCIENCE, INFORMATION SYSTEMS Security and Privacy Pub Date : 2023-02-26 DOI:10.1002/spy2.304
Unsub Zia, M. McCartney, B. Scotney, Jorge Martínez, Ali Sajjad
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Abstract

The strength of cryptographic keys rely on the random number generators (RNGs) to produce random seed values. Unfortunately there are not many RNGs options suitable for Internet of Things (IoTs) scenario, due to limited processing resources and bulk quantity of IoT data that needs to be secured. In this article, we studied sawtooth map which is a chaotic map. However, when implemented on a computer, the sawtooth map results on a non‐chaotic orbit due to the finite precision of computation. This can be avoided if we use the sawtooth map as the local map in a coupled map lattice (CML) system. We explore such coupled map systems for randomness through entropy and statistical analysis. Based on the results, we propose a lightweight hybrid pseudo random number generator (PRNG) based on sawtooth based CML system and SPONGENT hashing. The proposed PRNG is thoroughly tested against statistical attacks, entropy analysis, key space analysis and compared with existing state of the art solutions. The results provide evidence that the proposed PRNG produces random numbers that could produce sufficiently strong cryptographic keys for resource constrained IoT devices.
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基于锯齿映射的物联网资源高效伪随机数生成器
密钥的强度依赖于随机数生成器(rng)产生随机种子值。不幸的是,由于有限的处理资源和需要保护的大量物联网数据,适合物联网(IoT)场景的rng选项并不多。本文研究的是锯齿图,它是一种混沌图。然而,当在计算机上实现时,由于计算精度有限,锯齿形映射在非混沌轨道上产生。如果我们在耦合映射格(CML)系统中使用锯齿形映射作为局部映射,则可以避免这种情况。我们通过熵和统计分析来探索这种随机耦合映射系统。在此基础上,我们提出了一种基于锯齿状CML系统和海绵哈希的轻量级混合伪随机数生成器(PRNG)。提出的PRNG对统计攻击、熵分析、密钥空间分析进行了彻底的测试,并与现有的最先进的解决方案进行了比较。结果证明,所提出的PRNG产生的随机数可以为资源受限的物联网设备产生足够强的加密密钥。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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