Title :
Application of multilayer perceptron networks in symmetric block ciphers
Author :
Yee, Liew Pol ; De Silva, Liyanage C.
Author_Institution :
Dept. of Electr. & Comput. Eng., Nat. Univ. of Singapore, Singapore
fDate :
6/24/1905 12:00:00 AM
Abstract :
In this paper, the applicability of using multilayer perceptron (MLP) networks in symmetric block ciphers is explored. A prototype symmetric block cipher is proposed. It employs an MLP network that decides on the algorithm used for encryption. The MLP network is, in turn, dependent on the secret key. By employing a mutation algorithm comprised of cryptographically proven modular arithmetic and Feistel networks, it is hoped that such a symmetric block cipher will be resistant to modern cryptanalytic attacks, such as differential and linear attacks
Keywords :
arithmetic; cryptography; evolutionary computation; multilayer perceptrons; Feistel networks; cryptanalytic attacks; cryptographically proven modular arithmetic; differential attacks; encryption algorithm; key-dependent cryptographic algorithm; linear attacks; multilayer perceptron neural networks; mutation algorithm; secret key; symmetric block ciphers; Application software; Arithmetic; Cryptography; Design engineering; Drives; Intelligent networks; Multilayer perceptrons; Neural networks; Partitioning algorithms; Prototypes;
Conference_Titel :
Neural Networks, 2002. IJCNN '02. Proceedings of the 2002 International Joint Conference on
Conference_Location :
Honolulu, HI
Print_ISBN :
0-7803-7278-6
DOI :
10.1109/IJCNN.2002.1007731