Distributed intrusion detection method of vehicle ad hoc network

Abstract

The invention provides a distributed intrusion detection method of a vehicle ad hoc network. Local detection is started by adopting a Naive Bayesian classification algorithm by vehicle nodes; when an abnormal condition is detected, data are marked to be abnormal and are stored into a local feature library; response measures are immediately adopted by a local response module; meanwhile, abnormal warning is sent out to adjacent nodes and abnormal features are transmitted to the adjacent nodes through an on-line response module, if the adjacent nodes are also abnormal, the abnormal features are transmitted to the local feature library, and response measures are immediately adopted by the local response module; and meanwhile, the abnormal warning is sent to other adjacent nodes and the abnormal features are transmitted to the other adjacent nodes except source nodes of abnormal warning through the on-line response module; and abnormal warning and abnormal feature transmission are continuously passed through the manner, so that distributed intrusion detection of the whole vehicle ad hoc network is realized. With the adoption of the distributed intrusion detection method of the vehicle ad hoc network, analysis and detection ability of the whole vehicle ad hoc network is improved; and the distributed intrusion detection method has the characteristic of being simple in system structure, low in complexity, strong in learning and high in intelligentization degree.

Description

technical field [0001] The invention relates to the field of vehicular ad hoc networks, in particular to an intrusion detection method for vehicular ad hoc networks. Background technique [0002] The vehicle-mounted ad hoc network takes the vehicle as the basic information unit, and ensures vehicle driving safety, avoids road congestion and improves travel comfort through real-time information interaction between vehicles and between vehicles and roadside facilities. The security mechanism of the vehicular ad hoc network can be divided into a prevention-based security mechanism and a detection-based security mechanism. Among them, the prevention-based security mechanism mainly refers to access control realized by key management and authentication, while the detection-based security mechanism mainly refers to intrusion detection. Usually, prevention-based defense strategies are powerless to those malicious nodes that have joined the VANET. As a detection-based security mech...

AI Technical Summary

Problems solved by technology

Among them, the intrusion detection method based on the naive Bayesian classifier has the characteristics of good classification effect and strong robustness, and can estimate the necessary parameters according to a small amount of training data, but there are some problems when it is directly applied to the vehicle self-organizing network. limitations, such as: the probability of events that have not occurred in the training set is not considered; the continuous attributes in the data cannot be directly processed, etc.

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