Work place: Mathematics Department, Faculty of Science Mansoura University, Mansoura 35516, Egypt
E-mail: ymafouda@mans.edu.eg
Website: https://orcid.org/0000-0002-5236-0708
Research Interests:
Biography
Yasser M. Fouda received the B.Sc. degree in statistics and scientific computation from Mansoura University, Egypt, in (1992). He is appointed as a teaching assistant from this year till (1996). Then, he obtained his M.Sc. and Ph.D. degrees of computer science from Mansoura University in (1997) and (2002), respectively. He is currently associate professor of computer science in the computer science division/Mathematics Department, Faculty of Science, Mansoura University, Egypt. From (2005) to (2015), he was assistant professor with college of computer science and information technology, KFU University, KSA. His research interest includes computer vision, artificial neural networks, pattern recognition, medical images, image encryption, image watermarking, chaos theory, and image processing and its application in industry. He published over 20 peer-reviewed articles in reputable journals and conferences, and he co-advised 11 M.Sc. and Ph.D. students.
By Shimaa A. Elanany Abdelrahman A. Karawia Yasser M. Fouda
DOI: https://doi.org/10.5815/ijwmt.2025.01.01, Pub. Date: 8 Feb. 2025
The integration of chaos theory and orthogonal moments has gained significant traction in contemporary image analysis. This paper presents a novel approach to image encryption and decryption, leveraging a modified logistic chaotic map and discrete orthogonal moments. The coefficients derived from Charlier polynomials and the image function are utilized to obfuscate the plaintext image. Furthermore, to bolster security measures, the pixel values of the obfuscated image are shuffled employing a modified logistic chaotic map. The encryption key is constructed from the parameters of both the chaotic map and Charlier polynomials, enhancing the robustness of the encryption scheme. Extensive experimental validation is conducted to assess the security of the proposed image encryption algorithm. Results demonstrate a considerable deviation in pixel values following diffusion via Charlier moments’ coefficients. Statistical tests and comprehensive security analyses affirm the resilience of the proposed algorithm against data loss attacks. The experimental result with Pearson correlation coefficient is almost 0, key space is greater than 2^210, and information entropy can reach 7.8404, which establish its superior security posture relative to existing algorithms within the domain of image encryption. The findings underscore the efficacy and reliability of the proposed scheme, positioning it as a viable solution for safeguarding sensitive image data in various applications.
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