Title :
Using genetic algorithm to find near collisions for the compress function of Hamsi-256
Author :
Li, Yun-Qiang ; Ai-Ian, Wang
Author_Institution :
Electron. Tech. Inst., Inf. Eng. Univ., Zhengzhou, China
Abstract :
Hamsi is one of 14 remaining candidates in NIST´s Hash Competition for the future hash standard SHA-3 and Hamsi-256 is one of four kinds of Hamsi. In this paper we present a genetic algorithm to search near collisions for the compress function of Hamsi-256, give a near collision on (256 - 20) bits and a near collision on (256 - 21) bits with four differences in the chaining value, and obtain a differential path for three rounds of Hamsi-256 with probability 2-24, 2-23 respectively, which are better than previous work reported about near collisions.
Keywords :
cryptography; genetic algorithms; probability; Hamsi-256; chaining value; compress function; genetic algorithm; hash competition; hash standard SHA; near collision; probability; Cryptography; Genetic Algorithm; Hamsi; hash function; near collisions; the SHA-3 hash function competition; the compress function of Hamsi-256;
Conference_Titel :
Bio-Inspired Computing: Theories and Applications (BIC-TA), 2010 IEEE Fifth International Conference on
Conference_Location :
Changsha
Print_ISBN :
978-1-4244-6437-1
DOI :
10.1109/BICTA.2010.5645231