Wireless network interference attack scene identification method based on distance measurement

Abstract

The invention discloses a wireless network interference attack scene identification method based on distance measurement, which can accurately classify interference attack scenes. The wireless networkinterference attack scene identification method comprises the steps of (10) obtaining an interference attack clustering center: setting different attack scenes, collecting message interaction processdata of a current node and a neighbor node for each attack scene to form an offline measurement vector set, and calculating the interference attack clustering center of the attack scene based on theset; (20) forming an on-line measurement vector: collecting message interaction process data of the node and a neighbor node on line to form the on-line measurement vector; and (30) determining an interference attack scene: calculating the distance from the online measurement vector of the node to each interference attack clustering center, and outputting the interference attack scene corresponding to the interference attack clustering center with the minimum distance as an identification 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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