A joint intrusion detection method for wsns based on dangerous multi-agent

Abstract

The invention discloses a WSNs united intrusion detection method based on multiple danger agents. One IDS agent is implanted on each node in the WSNs, a peer-peer relation is built between the IDS agents, the nodes perceiving the danger are set to be the main IDS agents, other nodes for detection in the danger areas are set to be the local IDS agents, and each IDS agent comprises a plurality of function agents. The local IDS agents are responsible for collecting local data and detecting abnormal data, and the main IDS agents are responsible for processing a detection result in a concentrated mode and finally determining the malicious nodes. The method fully considers the characteristics of the WSNs, the detection efficiency is improved, the detection energy consumption of the whole network is saved, and the service life of the network is prolonged.

Description

technical field [0001] The invention relates to the technical field of WSNs security, in particular to a method for combined intrusion detection of WSNs based on dangerous multi-agents. Background technique [0002] WSNs intrusion detection technology is mainly researched from the two aspects of detection system and detection algorithm, trying to reduce energy consumption while enhancing the effectiveness and security of intrusion detection by designing an intrusion detection system or intrusion detection algorithm suitable for WSNs characteristics. According to the relationship between detection nodes, WSNs intrusion detection system is mainly divided into three types: distributed, peer-to-peer collaborative and hierarchical. Among them, a single node in the distributed system is equipped with a complete intrusion detection system, and each node does not cooperate with each other, and performs intrusion behavior detection independently, while the peer-to-peer collaborative ...

AI Technical Summary

Problems solved by technology

[0005] In the previous WSNs intrusion detection method based on the dangerous multi-agent system, the nodes receiving the dangerous signal in the dangerous domain need to collect network-related antigen information, and the nodes that perceive and send out the dangerous signal need to centralize the extracted antigen information. Intrusion detection uses a self / non-self detection method that requires a large number of sample training. This method needs to obtain a large number of original antigens, and the training time is long and the training cost is large.

At the same time, the transmission of a large amount of antigen information will increase the communication load of the network and the communication consumption of nodes.

The node in the network that perceives danger corresponds to the "suffering node" in the biological immune system. It is a node that is on the verge of extinction and must be damaged in terms of node resources. If the node continues to perform expensive detection operations, obviously is unreasonable

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