期刊名称：International Journal of Advanced Networking and Applications
电子版ISSN：0975-0290
出版年度：2010
卷号：2
期号：1
页码：437-444
出版社：Eswar Publications
摘要：We can generate a secret key using neural cryptography, which is based on synchronization of Tree Parity Machines (TPMs) by mutual learning. In the proposed TPMs random inputs are replaced with queries which are considered. The queries depend on the current state of A and B TPMs. Then, TPMs hidden layer of each output vectors are compared. That is, the output vectors of hidden unit using Hebbian learning rule, left-d ynamic hidden unit using Random walk learning rule and right-dynamic hidden unit using Anti-Hebbian learning rule are compared. Amo ng the compared values, one of the best values is received by the output layer. The queries fix the security against majority flipping and geometric attacks are shown in this paper. The new parameter H can accomplish a higher level of security for the neural key-exchange protocol without altering the average synchronization time
关键词：Majority attacks; Neural Synchronization; Queries; Tree Parity Machines
