Identifying local trust value with neural network in P2P environment

Global trust value of P2P (peer-to-peer) has been studied in detail, but the base of it, local trust value, has not been explored in depth. The existent models only adopt simple methods to calculate it. These methods are based on count of success and failure times of transaction, so it cannot represent the distribution of success and failure in transaction history. It is the first time to introduce neural network to identify the local trust value in P2P environment. Transaction result sequence that can represent the transaction history is used as input of neural network to identify local trust value. The structure of neural network, method of input standardization and training sample constructing are presented. Analysis and experiment show that it is feasible and effective to identify local trust value with neural network in P2P environment