METHOD OF STATISTICAL ANALYSIS OF RANDOM SEQUENCES GENERATED BY GENERATORS OF RANDOM AND PSEUDO-RANDOM NUMBER

Abstract

The problems of the Internet of Things, in particular the need to protect confidential data, lead to the use of encryption and decryption methods, which, in turn, rely on the use of random numbers. The use of HVDC can help ensure the security of this process, but it is important to use high-quality HVDC and thoroughly test them to avoid security vulnerabilities. Statistical analysis is used to assess the randomness of the generated sequences by testing them using statistical tests of randomness. These tests evaluate various statistical properties, such as the frequency distribution of the generated numbers, the distribution of consecutive numbers, and the presence of patterns. By performing a statistical analysis, you can identify any flaws or biases in the operation of the random number generator and improve its quality. The article checks the sequence for randomness using two- and three-dimensional statistics. A mathematical model is built, a theorem is given. A scheme of statistical analysis of sequences was built, based on which software engineering methods were used. Examples of using binary statistics for bit sequence analysis are given. The use of statistical analysis of the randomness of sequences generated by random (or pseudo-random) number generators is a popular trend, as it is critical to the reliability and security of various computing systems and applications, including the Internet of Things (IoT), cryptography, simulations, and scientific calculation. With the growing importance of cybersecurity and data privacy, the demand for reliable and secure random number generators is increasing, and the use of statistical analysis to assess the randomness of sequences generated by random (or pseudo-random) number generators is becoming increasingly critical.