Network Intrusion Detection Based on Explainable Artificial Intelligence

People often use similar methods to invade network traffic, such as flood attacks and Ddos attacks. Early detection of malicious traffic usually uses manual filtering to establish a whitelist, and then uses some artificial intelligence to simply measure some characteristic parameters. The high predi...

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Bibliographic Details
Published in:Wireless personal communications 2023-07, Vol.131 (2), p.1115-1130
Main Authors: Wang, Yiwen, Xu, Lei, Liu, Wanli, Li, Rongzhen, Gu, Junjie
Format: Article
Language:English
Subjects:
Communications Engineering
Communications traffic
Computer Communication Networks
Engineering
Explainable artificial intelligence
Intrusion detection systems
Networks
Performance prediction
Signal,Image and Speech Processing
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Summary:People often use similar methods to invade network traffic, such as flood attacks and Ddos attacks. Early detection of malicious traffic usually uses manual filtering to establish a whitelist, and then uses some artificial intelligence to simply measure some characteristic parameters. The high predictive performance of artificial intelligence will inevitably introduce unknowable decision process into network intrusion detection. When it is applied to the extremely important network environment, human’s doubt on its black box effect will hinder its advancement. Here, we make a propose to come up with a network traffic intrusion detection method (XAI-IDS) on account of interpretable artificial intelligence to detect malicious traffic intrusion in networks. XAI-IDS analyzes network traffic data to predict whether the traffic is malicious intrusion.
ISSN:0929-6212
1572-834X
DOI:10.1007/s11277-023-10472-7