Cryptographic Grade Chaotic Random Number Generator Based on Tent-Map

被引:5
作者
Al-Daraiseh, Ahmad [1 ]
Sanjalawe, Yousef [2 ]
Al-E'mari, Salam [3 ]
Fraihat, Salam [4 ]
Taha, Mohammad Bany [5 ]
Al-Muhammed, Muhammed [1 ]
机构
[1] Amer Univ Madaba, Sch Informat Technol, Comp Sci Dept, Amman 11821, Jordan
[2] Amer Univ Madaba, Sch Informat Technol, Cybersecur Dept, Amman 11821, Jordan
[3] Univ Petra, Fac Informat Technol, Informat Secur Dept, Amman 11196, Jordan
[4] Ajman Univ, Coll Engn & Informat Technol, Artificial Intelligence Res Ctr AIRC, POB 346, Ajman, U Arab Emirates
[5] Amer Univ Madaba, Sch Informat Technol, Dept Data Sci & Artificial Intelligence, Amman 11821, Jordan
关键词
random number generator; Tent-Map; chaotic; Dieharder; CRYPTOSYSTEM;
D O I
10.3390/jsan12050073
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
In recent years, there has been an increasing interest in employing chaotic-based random number generators for cryptographic purposes. However, many of these generators produce sequences that lack the necessary strength for cryptographic systems, such as Tent-Map. However, these generators still suffer from common issues when generating random numbers, including issues related to speed, randomness, lack of statistical properties, and lack of uniformity. Therefore, this paper introduces an efficient pseudo-random number generator, called State-Based Tent-Map (SBTM), based on a modified Tent-Map, which addresses this and other limitations by providing highly robust sequences suitable for cryptographic applications. The proposed generator is specifically designed to generate sequences with exceptional statistical properties and a high degree of security. It utilizes a modified 1D chaotic Tent-Map with enhanced attributes to produce the chaotic sequences. Rigorous randomness testing using the Dieharder test suite confirmed the promising results of the generated keystream bits. The comprehensive evaluation demonstrated that approximately 97.4% of the tests passed successfully, providing further evidence of the SBTM's capability to produce sequences with sufficient randomness and statistical properties.
引用
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页数:26
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