NDLI: Identifying local trust value with neural network in P2P environment

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Identifying local trust value with neural network in P2P environment

Content Provider	IEEE Xplore Digital Library
Author	Huang Baohua Hu Heping Lu Zhengding
Copyright Year	2005
Description	Author affiliation: Coll. of Comput. Sci. & Technol., Huazhong Univ. of Sci. & Technol. (Huang Baohua; Hu Heping; Lu Zhengding)
Abstract	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
File Size	188165
File Format	PDF
ISBN	0780391799
DOI	10.1109/CANET.2005.1598194
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2005-09-26
Publisher Place	Kyrgyzstan
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Peer to peer computing Scalability Standardization Educational institutions Neural network History Trust P2P Computer science Authorization Intelligent networks Network servers Neural networks
Content Type	Text
Resource Type	Article

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