Scenario recognition method of wireless network interference attack based on distance measure

Abstract

The invention discloses a wireless network interference attack scene recognition method based on distance measurement, which can accurately classify interference attack scenes. The wireless network interference attack scene identification method of the present invention comprises the following steps: (10) Acquisition of the interference attack clustering center: different attack scenes are set, and for each attack scene, the message interaction process data of the node and the neighbor node are collected , forming an offline measure vector set, and based on this set, calculate the interference attack clustering center of the attack scenario; (20) Online measure vector formation: collect the message interaction process data between the node and the neighbor node online, and form an online measure vector; (30) Jamming attack scene determination: Calculate the distance from the online measurement vector of this node to each jamming attack cluster center, and output the jamming attack scene corresponding to the jamming attack cluster center with the smallest distance as the recognition result.

Description

technical field [0001] The invention belongs to the technical field of network data communication, in particular to a distance measurement-based wireless network interference attack scene recognition method. Background technique [0002] Jamming attacks refer to attacks that prevent legitimate users from using wireless channels to send and receive messages by sending useless interference signals to wireless communication channels, or destroying the operation process of wireless network link layer access protocols. According to different behavior strategies, interference attacks can be divided into various attack types, such as persistent interference sources, random interference sources, CTS packet attacks, DATA packet attacks, and ACK packet attacks. Persistent interference sources continue to send useless interference signals to the wireless channel, thereby preventing legitimate users from accessing the channel; random interference sources send interference signals to the...

AI Technical Summary

Problems solved by technology

However, the existing methods are often difficult to apply to the classification of various jamming attack scenarios, and have high transmission overhead and long recognition delay

[0004] Existing wireless network jamming attack scene recognition methods cannot solve the problem of classifying multiple types of jamming attack scenarios at the same time, and it is difficult to deal with multiple types of jamming attack scenarios, and the overhead is large and the accuracy is low

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