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Proceedings of the 2nd International Symposium on Information Processing (ISIP 2009)

Huangshan, China, August 21-23, 2009

Editors: Fei Yu, Jian Shu, and Guangxue Yue

AP Catalog Number: AP-PROC-CS-09CN002

ISBN: 978-952-5726-02-2 (Print), 978-952-5726-03-9 (CD-ROM)

Page(s): 290-293

Sub-optimum Analysis and Trusted Network

Zengtang Qu and Ping He

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The paper describes sub-optimum method for trusted computing models of network security. trusted computing of network security is performed under both optimum and non-optimum learning. The task of selection is done using a knowledge-based network under sub-optimum degree learning. The methodology for trusted models involves minimization of non-optimum and maximization of optimum, defined in term of sub-optimum degree evaluation indices, in connectionist framework. For the non-optimum analysis method, the algorithm does not need know the number of cluster a priori. It is considered that the non-optimum network does not exclude the targets and the results of sub-optimum in practice. The formation of non-optimum network serves as the basis for existence of optimum network in uncertainty. Besides, the various characteristics and functions of the non--optimum network can be measured from the sub-optimum network. By summing the practice, this paper has also come at sub-optimum principle of the network, established the conception of sub-optimum thresholds and put forward three theorems about sub-optimum parameters. Through the concept of sub-optimum, Finally, it analyzes the actual significance of trusted network.

Index Terms

Sub-optimum analysis; trusted computing; trusted network; self-organization; sub-optimum decision making

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