A trust evaluation method for unweighted nodes based on clustering in uasns

Abstract

The invention discloses a weightless node trust evaluation method based on clustering in UASNs. By observing the behavior of nodes in a certain period, the communication characteristics, energy characteristics, neighbor characteristics and data characteristics of nodes are calculated, and then the node's communication characteristics, energy characteristics, neighbor characteristics and data characteristics are estimated. Local trust and global trust, among which, communication features and data features are collectively called security trust, representing the security of nodes, energy characteristics and neighbor characteristics are collectively called available trust, representing the availability of nodes, communication characteristics, energy characteristics and neighbor characteristics are represented by Local node calculation, data features are calculated by the surface data center, AUV is used in the process of sensing data and trust information transmission to reduce the energy consumption of network nodes, the joint analysis of the four trust features obtains the local trust and global trust of the node, which is used to filter the network Trusted nodes and untrusted nodes in the network, and used to select trusted next-hop nodes, thereby improving the accuracy of trust assessment, protecting the security of the network, and prolonging the life of the network.

Description

technical field [0001] The invention belongs to the technical field of underwater acoustic sensor networks, and in particular relates to a cluster-based trust evaluation method for unweighted nodes in UASNs. Background technique [0002] Underwater Acoustic Sensor Networks (UASNs) is a wireless network formed by self-organization of multiple types of nodes such as multi-functional miniature underwater sensor nodes and underwater autonomous vehicles (AUV) with acoustic communication links. With its self-organization and diverse data Perception and other characteristics are widely used in various fields such as environmental monitoring, military monitoring, and space exploration, and have gradually become one of the hotspots in the research field. However, it is followed by diverse security requirements. Compared with land wireless sensor networks, the security threats faced by underwater acoustic sensor networks are more difficult to solve. caused by attributes. [0003] Th...

AI Technical Summary

Problems solved by technology

In the existing trust management mechanism, the node trust evaluation method mostly adopts the linear weighting calculation method. However, in the underwater dynamic environment, the optimal weight in the linear weighting method is difficult to determine, and the non-optimal weight will affect the node trust evaluation. the accuracy of

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