Abstract

Internet of Things (IoT) devices collect some volumes of data, some of which will require protection based on sensitivity or compliance requirements. IoT data protection solutions must span edge to cloud, provide scalable encryption and key management, and not impede data analysis. An analysis of recent research and publications shows a great deal of interest in finding various ways to develop lightweight pseudorandom number generators that have been widely used on the Internet of Things or mobile devices. These so-called lightweight IoT devices have limited power, space, and computing resources. Therefore, there is a huge need to develop and test the quality of lightweight pseudorandom number generators, which is an important component of cybersecurity. The available approaches to testing random or pseudorandom sequences show low flexibility and versatility in the means of finding hidden patterns in the data. It is revealed that for sequences of length up to 100 bits there are not enough existing statistical packets. The available techniques show low flexibility and versatility in the means of finding hidden patterns in the data. Perspective direction of research — static testing of sequences using multidimensional statistics is considered. To solve this problem, it is suggested to use algorithms based on multidimensional statistics. In the work, formulas are given and theorem for testing sequences for randomness, using two or three-dimensional statistics that can be used for small and medium-sized sequences is formulated. The new technique of PRS testing is proposed in the paper, and several criteria for testing bit sequence of small length are considered, which, in comparison with one-dimensional statistics, gives a more accurate result. As a result of the implementation of this technique, an information system can be created that will allow analyzing the PRS of a small length and choosing a quality PRS for use in the Internet of Things Security.

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