Sensor network trust evaluation method based on node behaviors and D-S evidence theory
A sensor network and evidence theory technology, applied in the field of security trust assessment in wireless sensor networks, can solve the problems of easy loss, difficult identification of malicious nodes, and "difficult trust value"
Inactive Publication Date: 2013-10-23
BEIHANG UNIV
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[0006] 1. Purpose: The purpose of the present invention is to provide a sensor network trust evaluation method based on node behavior and D-S evidence theory, which embodies the characteristics of "difficult to obtain and easy to lose" trust value, and solves the problem that malicious nodes in the network are difficult to identify , put an end to the information leakage problem caused by internal nodes being captured, and ensure the security of network data transmission
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[0092] The present invention will be further described in detail below in conjunction with the accompanying drawings.
[0093] The sensor network trust evaluation method based on node behavior and D-S evidence theory provided by the present invention is suitable for sensor network systems with self-organizing characteristics; in order to avoid the inter-node trust calculation from entering an infinite loop state, the evaluation node (subject) only calculates the two-hop The trust value of the evaluated node (object); first, use the statistics of node behavior in unit time t to determine various trust factors, and obtain the direct and indirect trust value of the evaluated node respectively; then, according to the direct and indirect trust value pair The membership relationship of the fuzzy set forms the basic input vector of the evidence theory; finally, according to the evidence difference between the indirect trust value and the direct trust value, the Damper combination rule...
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The invention discloses a sensor network trust evaluation method based on node behaviors and a D-S evidence theory, comprising the following five steps: 1) designing various trust factor strategies for nodes in a wireless sensor network; 2) setting trust factor weights according to network application scenes and simultaneously calculating the node behavior coefficient mu to obtain the direct trust value and multiple indirect trust value of an evaluated object; 3) calculating a fuzzy subset membership function for each trust value by utilizing the concepts of membership and linguistic variables of a fuzzy set theory, performing fuzzy classification on the various the trust values to form the basic confidence function of the D-S evidence theory; 4) calculating the evidence difference of the direct trust value and the indirect trust values of the evaluated node and altering the weights of the indirect trust values; and 5) adopting the Dempster synthesis rule to obtain the comprehensive trust value of the evaluated node and a final basic confidence designated value according to the altered trust weights. The invention solves the problem of difficult identification of malicious nodes in a network and ensures the safety of network data transmission.
Description
(1) Technical field [0001] The invention relates to a mutual trust evaluation method between adjacent nodes based on node behavior strategy and D-S evidence theory, in particular to a sensor network trust evaluation method based on node behavior and D-S evidence theory. It belongs to the technical field of security trust evaluation in wireless sensor networks. (2) Background technology [0002] Wireless sensor networks (WSNs for short) integrate sensor technology, micro-electromechanical system (MEMS) technology, embedded computing technology, wireless communication technology and distributed information processing technology. Processing, communication and management functions can be applied to industrial control and monitoring, home automation and consumer electronics, security and military, material tracking and supply chain management, smart agriculture, environmental perception and health monitoring, etc. [0003] With the increasing complexity of WSNs applications, the...
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IPC IPC(8): H04W12/12H04W84/18H04W12/122
Inventor 冯仁剑万江文许小丰吴银锋于宁
Owner BEIHANG UNIV