Title :
Pseudorandom generator based on clipped Hopfield neural network
Author :
Chan, Chi-Kwong ; Cheng, L.M.
Author_Institution :
Dept. of Electron. Eng., Hong Kong City Univ., Hong Kong
Abstract :
We present a new construction of a pseudorandom generator based on a single linear feedback shift register and a clipped version of Hopfield neural network. The clipped Hopfield neural network (CHNN) acts as a nonlinear filter function, which destroys the linearity and algebraic structure of the LFSR. The resulting sequences have long period and large linear complexity. The construction is suitable for practical implementation of efficient stream cipher cryptosystems
Keywords :
Hopfield neural nets; binary sequences; computational complexity; cryptography; random number generation; shift registers; clipped Hopfield neural network; linear complexity; linear feedback shift register; nonlinear filter function; pseudorandom generator; sequences; stream cipher cryptosystems; Cryptography; Filtering; Hopfield neural networks; Linear feedback shift registers; Linearity; Magnetohydrodynamics; Neural networks; Nonlinear equations; Nonlinear filters; Symmetric matrices;
Conference_Titel :
Circuits and Systems, 1998. ISCAS '98. Proceedings of the 1998 IEEE International Symposium on
Conference_Location :
Monterey, CA
Print_ISBN :
0-7803-4455-3
DOI :
10.1109/ISCAS.1998.703946
