Applying Neural Networks for Simplified Data Encryption Standard (SDES) Cipher System Cryptanalysis
Khaled Alallayah1, Mohamed Amin2, Waiel AbdElwahed3, and Alaa Alhamami4
1Department of Computer Science, IBB University, Yemen
2Department of Mathematical and Computer Science, El-Menoufia University, Egypt
3Department of Operation Research and Decision, El-Menoufia University, Egypt
4Faculty of Computing Studies, Amman Arab University for Graduate Studies, Jordan
1Department of Computer Science, IBB University, Yemen
2Department of Mathematical and Computer Science, El-Menoufia University, Egypt
3Department of Operation Research and Decision, El-Menoufia University, Egypt
4Faculty of Computing Studies, Amman Arab University for Graduate Studies, Jordan
Abstract: The problem in cryptanalysis can be described as an unknown and the neural networks are ideal tools for black-box system identification. In this paper, a mathematical black-box model is developed and system identification techniques are combined with adaptive system techniques, to construct the Neuro-Identifier. The Neuro-Identifier is discussed as a black-box model to attack the target cipher systems. In this paper a new addition in cryptography has been presented and the methods of block Simplified DES (SDES) crypto systems are discussed. The constructing of Neuro-Identifier mode is to achieve two objectives: the first one is to emulator construction Neuro-model for the target cipher system, while the second is to (cryptanalysis) determine the key from given plaintext-ciphertext pair.
Keywords: System Identification, artificial neural network, emulation, SDES, cryptanalysis, and neuro-identifier.
Received July 19, 2009; accepted May 20, 2010.
