2 results
Search Results
Now showing 1 - 2 of 2
Article Cryptographic Randomness Testing of Block Ciphers: SAC Tests(IEEE-Inst Electrical Electronics Engineers Inc, 2026) Aslan, Melis; Doganaksoy, Ali; Kocaman, Sermin; Saygi, Zulfukar; Sulak, FatihBlock ciphers are designed to function as random mappings, making it essential for them to successfully pass statistical randomness tests. These tests evaluate whether the distribution of a test statistic, derived empirically through various data manipulations over states of the algorithm, aligns with the theoretical distribution for cryptographic randomness. Beyond this, evaluating the cryptographic properties of the algorithm is also important to ensure its security and reliability. One of the important cryptographic randomness properties is the Strict Avalanche Criterion (SAC), which assesses the impact of a one-bit alteration in the input over the output. In this work, we introduce new SAC-based tests to offer more reliable evaluation for the cryptographic randomness of block cipher algorithms. The tests are utilized for the application of AES, PRESENT, and CLEFIA block ciphers. The results are compared with Soto's evaluation methods, which are known for their comprehensive approach to block ciphers. According to this, it is apparent that our novel SAC tests improve upon Soto's results, thus providing a more comprehensive understanding of randomness.Article Nonparametric Tests for Comparing Reliabilities of Coherent Systems at Specific Mission Time(IEEE-Inst Electrical Electronics Engineers Inc, 2026) Xu, Xuan; Zhu, Xiaojun; Balakrishnan, Narayanaswamy; Ng, Hon Keung TonyReliability analysis of coherent systems is critical for evaluating the performance of systems whose functionality depends on the reliability of their components. Traditional parametric methods for comparing reliabilities of coherent systems assume a specific probability distribution for component lifetimes, which may result in inaccurate results when these model assumptions are violated. This article introduces nonparametric procedures using system-level data with known signatures to compare the reliabilities of systems. The proposed methodology avoids parametric distributional assumptions for component lifetimes while relying on the standard assumption in signature-based reliability analysis. Specifically, a two-sample likelihood ratio test procedure is proposed to demonstrate a component or system with superior reliability. Monte Carlo simulations are performed to evaluate the performance of the proposed methods. Furthermore, we examine the effect of system structure on test power and determine favourable structures to enhance the power performance of the test. Practical examples are used to illustrate the proposed test procedures.
