Attack of Against Simplified Data Encryption Standard Cipher System Using Neural Networks
Abstract
Problem statement: The problem in cryptanalysis can be described as an unknown and the neural networks are ideal tools for black-box system identification. In this study, a mathematical black-box model is developed and system identification techniques are combined with adaptive system techniques, to construct the Neuro-Identifier. Approach: The Neuro-Identifier was discussed as a black-box model to attack the target cipher systems. Results: In this study this model is a new addition in cryptography that presented the methods of block (SDES) crypto systems discussed. The constructing of Neuro-Identifier mode achieved two objectives: The first one was to construct emulator of Neuro-model for the target cipher system, while the second was to (cryptanalysis) determine the key from given plaintext-ciphertext pair. Conclusion: Present the idea of the equivalent cipher system, which is identical 100% to the unknown system and that means that an unknown hardware, or software cipher system could be reconstructed without known the internal circuitry or algorithm of it.
DOI: https://doi.org/10.3844/jcssp.2010.29.35
Copyright: © 2010 Khaled M. Alallayah, Waiel F. Abd El-Wahed, Mohamed Amin and Alaa H. Alhamami. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
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Keywords
- System identification
- artificial neural network
- emulation
- SDES
- cryptanalysis
- cipher system
- black box and neuro-identifier