A New Trend of Pseudorandom Number Generator Using Multiple Chaotic Systems

Saba, M. Ismail; Mohammed, Muamer N.; Ameedeen, Mohamed Ariff; Ahmed, Hussam

doi:10.1166/asl.2018.12949

Cited by 1 publication

(1 citation statement)

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“…In recent decades, chaos has been studied due to nonlinear and difficult to predict phenomenon in nature. Chaos has a great property that it is sensitive dependent on initial condition [3,4]. One of the most simple and famous chaotic map is logistic map, using this system many cryptographic application has been developed such as algorithm for image encryption and decryption, digital water marking algorithm and pseudo or true random number generator.…”

Section: Introductionmentioning

confidence: 99%

Cryptographic Pseudo-Random Bit Generator Based on New Combination Discrete Chaotic Systems

Hamid

Ahmad

Alhadawi

et al. 2021

Proceedings of International Conference on Emerging Technologies and Intelligent Systems

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Traditional 1-D discrete chaotic systems are not suitable to use directly in PRBG design for their cryptographic usage as their structures are simple and have predictability. Pseudo-random sequences have wide applications in image and video encryption, hash functions, spread spectrum communications, etc. In chaos-based cryptography, chaotic systems have been regarded as an important pseudorandom source in the design of pseudo-random bit generators due to its inherent properties of sensitive dependence on initial conditions and parameters. In order to improve the dynamism and features of standard logistic map, a 1-D discrete combination chaos model is proposed in this paper. The chaos model enables to construct new chaotic systems with combination of logistic map and Trigonometric functions. The performance analysis shows that the new systems are more complex and better than the original Logistic map. Further, we also propose to present a new pseudo-random bit generator based on new log-tan chaotic system and log-cot chaotic system. The randomness and other statistic analysis show that our pseudo-random bit generator has good randomness features, satisfy the linear complexity and balancedness requirements well.

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Section: Introductionmentioning

confidence: 99%