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An Improved Multi-Chaotic Public Key Algorithm Based on Chebyshev Polynomials

Authors :
Chunfu Zhang
Jing Bai
Yanchun Liang
Adriano Tavares
Lidong Wang
Tiago Gomes
Sandro Pinto
Source :
Algorithms, Vol 17, Iss 9, p 389 (2024)
Publication Year :
2024
Publisher :
MDPI AG, 2024.

Abstract

Due to the similar characteristics of chaotic systems and cryptography, public key encryption algorithms based on chaotic systems are worth in-depth research and have high value for the future. Chebyshev polynomials have good properties and are often used in the design of public key algorithms. This paper improves the Bose Multi-Chaotic Public Key Cryptographic Algorithm (BMPKC) by applying Chebyshev polynomials. The proposed algorithm (CMPKC-ki) introduces the selective coefficient ki based on the properties of Chebyshev polynomials, allowing the special functions that need to be negotiated in the original system to be freely and randomly chosen as Chebyshev polynomials, and can also be expanded to m levels. The improved cryptographic algorithm also utilizes chaotic hash functions and logistic mapping to generate pseudo-random sequences and overcomes shortcomings of the Bose algorithm by iteratively iterating the selected Chebyshev polynomials based on the number of 0s or 1s in the pseudo-random sequence, thus providing better security. Analysis and software testing results indicate that this algorithm has strong robustness against brute force attacks, achieving a higher attack time for breaking the private key compared to the CEPKC, BMPKC, and CMPKC algorithms. Compared to the CMPKC algorithm, our proposal algorithm achieves better performance in the encryption and decryption phases. Furthermore, we combine this Multi-Chaotic System Key Exchange Protocol with the Advanced Encryption Standard (AES) algorithm, while providing a demonstration, offering more possibilities for practical applications of this system.

Details

Language :
English
ISSN :
19994893
Volume :
17
Issue :
9
Database :
Directory of Open Access Journals
Journal :
Algorithms
Publication Type :
Academic Journal
Accession number :
edsdoj.bf36b8b9019742ce8dc3e4d6e27dd21b
Document Type :
article
Full Text :
https://doi.org/10.3390/a17090389