Title :
Hash function based on chaotic neural networks
Author :
Lian, Shiguo ; Liu, Zhongxuan ; Ren, Zhen ; Wang, Haila
Author_Institution :
SAMI Lab, France Telecom R&D Beijing
Abstract :
Chaos and neural networks have both been used in data encryption because of their cipher-suitable properties, such as parameter-sensitivity, time-varying, random-similarity, etc. Based on chaotic neural networks, a hash function is constructed, which makes use of neural networks´ diffusion property and chaos´ confusion property. This function encodes the plaintext of arbitrary length into the hash value of fixed length (typically, 128-bit, 256-bit or 512-bit). Its security against statistical attack, birthday attack and meet-in-the-middle attack is analyzed in detail. Its properties make it a suitable choice for data authentication
Keywords :
chaotic communication; cryptography; message authentication; neural nets; birthday attack; chaos; chaotic neural networks; cipher-suitable properties; confusion property; data authentication; data encryption; diffusion property; hash function; meet-in-the-middle attack; statistical attack; Algorithm design and analysis; Authentication; Chaos; Chaotic communication; Cryptography; Data security; Neural networks; Protection; Research and development; Telecommunications;
Conference_Titel :
Circuits and Systems, 2006. ISCAS 2006. Proceedings. 2006 IEEE International Symposium on
Conference_Location :
Island of Kos
Print_ISBN :
0-7803-9389-9
DOI :
10.1109/ISCAS.2006.1692566
