Department of Computer Science, University Carlos III of Madrid, 28911 Leganés, Spain.
Department of Electronic Technology, University Carlos III of Madrid, 28911 Leganés, Spain.
Sensors (Basel). 2018 Aug 21;18(9):2747. doi: 10.3390/s18092747.
Wireless Sensor Networks (WSNs) are a promising technology with applications in many areas such as environment monitoring, agriculture, the military field or health-care, to name but a few. Unfortunately, the wireless connectivity of the sensors opens doors to many security threats, and therefore, cryptographic solutions must be included on-board these devices and preferably in their design phase. In this vein, Random Number Generators (RNGs) play a critical role in security solutions such as authentication protocols or key-generation algorithms. In this article is proposed an avant-garde proposal based on the cardiac signal generator we carry with us (our heart), which can be recorded with medical or even low-cost sensors with wireless connectivity. In particular, for the extraction of random bits, a multi-level decomposition has been performed by wavelet analysis. The proposal has been tested with one of the largest and most publicly available datasets of electrocardiogram signals (202 subjects and 24 h of recording time). Regarding the assessment, the proposed True Random Number Generator (TRNG) has been tested with the most demanding batteries of statistical tests (ENT, DIEHARDERand NIST), and this has been completed with a bias, distinctiveness and performance analysis. From the analysis conducted, it can be concluded that the output stream of our proposed TRNG behaves as a random variable and is suitable for securing WSNs.
无线传感器网络（WSNs）是一项很有前途的技术，在环境监测、农业、军事领域或医疗保健等许多领域都有应用。不幸的是，传感器的无线连接为许多安全威胁打开了大门，因此，必须在这些设备上并最好在其设计阶段包含加密解决方案。在这方面，随机数生成器（RNG）在身份验证协议或密钥生成算法等安全解决方案中起着至关重要的作用。在本文中，提出了一种基于我们随身携带的心脏信号发生器（我们的心脏）的前卫提案，该提案可以使用医疗甚至具有无线连接的低成本传感器进行记录。特别是，为了提取随机位，已经通过小波分析进行了多级分解。该提案已经使用最大和最公开的心电图信号数据集之一（202 个主题和 24 小时的记录时间）进行了测试。关于评估，已经使用最苛刻的统计测试电池（ENT、DIEHARDER 和 NIST）对所提出的真随机数生成器（TRNG）进行了测试，并且已经完成了偏差、独特性和性能分析。从进行的分析中可以得出结论，我们提出的 TRNG 的输出流表现为随机变量，适用于保护 WSN。
