Automated Deep Learning BLACK-BOX Attack for Multimedia P-BOX Security Assessment by Zakaria Tolba (16904718)

“…<p>Resistance to differential cryptanalysis is a fundamental security requirement for symmetric block ciphers, and recently, deep learning has attracted the interest of cryptography experts, particularly in the field of block cipher cryptanalysis, where the bulk of these studies are differential distinguisher based black-box attacks. This paper provides a deep learning-based decryptor for investigating the permutation primitives used in multimedia block cipher encryption algorithms.We aim to investigate how deep learning can be used to improve on previous classical works by employing ciphertext pair aspects to maximize information extraction with low-data constraints by using convolution neural network features to discover the correlation among permutable atoms to extract the plaintext from the ciphered text without any P-box expertise. …”

Development of an Optimization Scheme for A Fixed-Wing UAV Long Endurance with PEMFC and Battery by Al Rayes, Zaid

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Parallel Algorithms for Distinguishing Nondeterministic Finite State Machines by Ali, Mustafa

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Modeling, testing, and regression testing of web applications. (c2006) by Al Shaar, Hamzeh K.

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Modeling and automated blackbox regression testing of web applications by Haraty, Ramzi

“…Having discovered, as well, that there is no automated black box regression testing technique, we also propose a methodology and algorithm to create a tool capable of applying black box regression testing automatically…”
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