Ahmed M. Ayoup^1,*, Ashraf A. M. Khalaf¹, Fahad Alraddady², Fathi E. Abd El-Samie³, Walid El-Safai^3,5, Salwa M. Serag Eldin^2,4

Intelligent Automation & Soft Computing, Vol.33, No.1, pp. 549-565, 2022, DOI:10.32604/iasc.2022.024379

Abstract This article introduces a new cancellable multi-biometric system based on the combination of a selective encryption method and a deep-learning-based fusion technology. The biometric face image is treated with an automatic face segmentation algorithm (Viola-Jones), and the image of the selected eye is XORed with a PRNG (Pseudo Random Number Generator) matrix. The output array is used to create a primary biometric template. This process changes the histogram of the selected eye image. Arnold’s Cat Map is used to superimpose the PRN pixels only on the pixels of the primary image. Arnold’s cat map deformed eyes are encrypted using the… More >

Osama M. Abu Zaid^1,*, Medhat A. Tawfeek^2,3, Saad Alanazi²

CMC-Computers, Materials & Continua, Vol.67, No.3, pp. 3161-3176, 2021, DOI:10.32604/cmc.2021.015175

Abstract This research presents, and clarifies the application of two permutation algorithms, based on chaotic map systems, and applied to a file of speech signals. They are the Arnold cat map-based permutation algorithm, and the Baker’s chaotic map-based permutation algorithm. Both algorithms are implemented on the same speech signal sample. Then, both the premier and the encrypted file histograms are documented and plotted. The speech signal amplitude values with time signals of the original file are recorded and plotted against the encrypted and decrypted files. Furthermore, the original file is plotted against the encrypted file, using the spectrogram frequencies of speech… More >