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All Journal International Journal of Electrical and Computer Engineering IAES International Journal of Artificial Intelligence (IJ-AI)
Hicham Grari
Chouaib Doukkali University
Computer Science & IT Electrical & Electronics Engineering Engineering

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A cryptanalytic attack of simplified-AES using ant colony optimization Hicham Grari; Ahmed Azouaoui; Khalid Zine-Dine
International Journal of Electrical and Computer Engineering (IJECE) Vol 9, No 5: October 2019
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (650.963 KB) | DOI: 10.11591/ijece.v9i5.pp4287-4295

Abstract

Ant colony Optimization is a nature-inspired meta-heuristic optimization algorithm that gained a great interest in resolution of combinatorial and numerical optimization problems in many science and engineering domains. The aim of this work was to investigate the use of Ant Colony Optimization in cryptanalysis of Simplified Advanced Encryption Standard (S-AES), using a known plaintext attack. We have defined the essential components of our algorithm such as heuristic value, fitness function and the strategy to update pheromone trails. It is shown from the experimental results that our proposed algorithm allow us to break S-AES cryptosystem after exploring a minimum search space when compared with others techniques and requiring only two plaintext-ciphertext pairs.
Cryptanalysis of Merkle-Hellman cipher using ant colony optimization Hicham Grari; Siham Lamzabi; Ahmed Azouaoui; Khalid Zine-Dine
IAES International Journal of Artificial Intelligence (IJ-AI) Vol 10, No 2: June 2021
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijai.v10.i2.pp490-500

Abstract

The Merkle-Hellman (MH) cryptosystem is one of the earliest public key cryptosystems, which is introduced by Ralph Merkle and Martin Hellman in 1978 based on an NP-hard problem, known as the subset-sum problem. Furthermore, ant colony optimization (ACO) is one of the most nature-inspired meta-heuristic optimization, which simulates the social behaviour of ant colonies. ACO has demonstrated excellent performance in solving a wide variety of complex problems. In this paper, we present a novel ant colony optimization (ACO) based attack for cryptanalysis of MH cipher algorithm, where two different search techniques are used. Moreover, experimental study is included, showing the effectiveness of the proposed attacking scheme. The results show that ACO based attack is more suitable than many other algorithms like genetic algorithm (GA) and particle swarm optimization (PSO).
Co-Authors Ahmed Azouaoui Khalid Zine-Dine Khalid Zine-Dine Siham Lamzabi