DocumentCode :
2481961
Title :
An improved algorithm for fast correlation attack on stream ciphers
Author :
Chen Wanzhi
Author_Institution :
Comput. Dept., Liaoning Tech. Univ., Huludao
fYear :
2008
fDate :
25-27 June 2008
Firstpage :
2126
Lastpage :
2129
Abstract :
Fast correlation attack on binary linear feedback shift registers (LFSR) in stream generators for stream ciphers applications are very paramount cryptanalytic techniques which are based on the idea from iterative probabilistic decoding procedures for binary symmetric channels (BSC). This paper presents an efficient correlation attack on stream ciphers, which is equivalent to solve the problem of recovering the LFSRpsilas initial state (u1, u2,hellip,un) from the observed output sequence z. I consider the problem as a decoding problem for a linear [N,L] code. In order to enhance the speed of correlation attack, the Walsh transform is used, in addition, I adopt the multi-thread method to deal with the parity checks. The novel scheme provides better performance and lower complicity, improves the efficiency of fast correlation attack.
Keywords :
Walsh functions; cryptography; iterative decoding; parity check codes; shift registers; Walsh transform; binary linear feedback shift registers; binary symmetric channels; cryptanalytic techniques; fast correlation attack; iterative probabilistic decoding procedures; multi-thread method; parity checks; stream ciphers; stream generators; Application software; Automation; Block codes; Cryptography; Educational institutions; Intelligent control; Iterative algorithms; Iterative decoding; Linear feedback shift registers; Parity check codes; cryptanalysis; fast correlation attack; linear feedback shift registers; parity checks; stream ciphers;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Intelligent Control and Automation, 2008. WCICA 2008. 7th World Congress on
Conference_Location :
Chongqing
Print_ISBN :
978-1-4244-2113-8
Electronic_ISBN :
978-1-4244-2114-5
Type :
conf
DOI :
10.1109/WCICA.2008.4593252
Filename :
4593252
Link To Document :
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