Method for detecting malicious node in wireless ad-hoc network based on behavioural cognition

Abstract

The invention discloses a method for detecting a malicious node in a wireless ad-hoc network based on behavioural cognition, and mainly solves the problem that the false detection rate is high due tothe fact that network congestion is not considered in the existing malicious node detection system. The implementation scheme comprises the steps of: periodically monitoring the working state information of a neighbour node by a node in a network; periodically performing quantitative trust evaluation on the neighbour node by the node; secondly judging whether a node having relatively low trust ispossibly congested in an evaluation period or not, so that false detection is prevented; calculating the direct trust; interacting with the neighbour node, and calculating the recommendation trust; synthesizing the direct trust and the recommendation trust, so that the total trust is obtained; and judging a malicious node, and isolating the malicious node. By means of the method for detecting themalicious node in the wireless ad-hoc network based on behavioural cognition in the invention, the possibility that a normal node is wrongly judged as a malicious node can be reduced; the negative effect of the malicious node on a network is reduced; the network reliability is improved; and the method can be used for detecting and defensing malicious node attack in the wireless ad-hoc network.

Description

technical field [0001] The invention belongs to the technical field of communication, and in particular relates to a malicious node detection method, which can be used for detecting and defending malicious node attacks in a wireless self-organizing network. Background technique [0002] A wireless ad hoc network is a multi-hop autonomous network formed by independent wireless temporary interconnection of wireless devices that do not depend on any fixed infrastructure. Due to the limited communication range of the nodes, the data transmission in the network needs to rely on cooperation with other intermediate nodes and adopt the method of multi-hop communication. Malicious nodes intruding into the network will attack the network by means of malicious packet loss, intentional delay, false routing, etc., resulting in a serious drop in network throughput or even network paralysis. In order to alleviate the dangers faced by the network, there are many methods based on cryptograp...

AI Technical Summary

Problems solved by technology

However, in a wireless ad-hoc network, due to the changeable network status, in addition to malicious behavior, network congestion, buffer overflow and other reasons may also cause network packet loss or high delay.

Credibility evaluation based only on packet loss rate and delay statistics can easily lead to a decrease in the credibility of non-malicious nodes, causing normal nodes to be misjudged as malicious nodes and move out of the network, which seriously affects the performance of wireless ad hoc networks

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