Dynamic lightweight class trust evaluation method based on Bayesian theory and entropy theory

Abstract

The invention provides a dynamic lightweight class trust evaluation method based on the Bayesian theory and the entropy theory, and belongs to the technical field of wireless sensor network security. The dynamic lightweight class trust evaluation method based on the Bayesian theory and the entropy theory includes the following steps: S1, an evaluation subject calculates the direct trust value of an evaluation object according to the Bayesian theory; S2, the evaluation subject updates the direct trust value of the evaluation object by means of attenuation factors and valid history memory periodically; S3, the evaluation subject calculates the confidence coefficient of the direct trust value of the evaluation object, and judges whether the confidence coefficient is larger than a certain threshold value to determine whether the indirect trust value of the evaluation object needs to be calculated or not; S4, the evaluation subject confirms the bang path of the recommendation trust values, confirms the weight of the recommendation trust values by means of the entropy theory, calculates the indirect trust value of the evaluation object, and calculates the comprehensive trust value of the evaluation object through the combination of the direct trust value and the indirect trust value of the evaluation object. The dynamic lightweight class trust evaluation method based on the Bayesian theory and the entropy theory is in accordance with the characteristics that sources such as capacity, calculation, and storage of network nodes are limited and has the advantages of being dynamic, adaptive, lightweight and the like.

Description

(1) Technical field [0001] The invention relates to a dynamic lightweight trust evaluation method based on Bayesian theory and entropy theory, which belongs to the technical field of wireless sensor network security, especially the technical field of trust management mechanism. (2) Background technology [0002] Wireless sensor networks (WSNs for short) use a large number of smart micro-sensor nodes with data collection and processing functions scattered randomly in the working area to cooperatively perceive, collect and process information about monitoring objects in the network coverage area. Jump wireless communication, send information to end users. Wireless sensor networks have the advantages of flexible networking and rapid deployment, and are widely used in many fields such as military security, precision agriculture, intelligent buildings, medical monitoring, environmental control, and biodiversity surveying. [0003] With the increasingly complex application of WSN...

AI Technical Summary

Problems solved by technology

These methods realize the evaluation of node trust value, identify malicious nodes to a certain extent, and provide a theoretical basis for subsequent research, but there are still the following problems: 1) the trust value is not considered when calculating the trust value. Due to the problem of dynamic and continuous changes, the evaluation method is not dynamic enough; 2) The determination of the weight of the indirect trust value often adopts the method of weighted average or subjective judgment, and the evaluation method is not adaptive; 3) The calculation of the comprehensive trust value is mostly simple The weighted sum of the direct trust value and the indirect trust value results in a large amount of calculation, which does not meet the lightweight requirements of trust evaluation

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