Using Explainable AI for Neural Network-Based Network Attack Detection

被引：0
|
作者：
Zou, Qingtian [1 ]
Zhang, Lan [2 ]
Sun, Xiaoyan [3 ]
Singhal, Anoop [4 ]
Liu, Peng [5 ,6 ]
机构：
[1] Penn State Univ, State Coll, PA 16803 USA
[2] No Arizona Univ, Flagstaff, AZ 86011 USA
[3] Worcester Polytech Inst, Dept Comp Sci, Worcester, MA 01609 USA
[4] NIST, Comp Secur Div, Gaithersburg, MD 20899 USA
[5] Penn State Univ, CyberSecur, State Coll, PA 16803 USA
[6] Penn State Univ, Cyber Secur Lab, State Coll, PA 16803 USA
来源：
COMPUTER | 2024年 / 57卷 / 05期
关键词：
Compendex;
D O I：
10.1109/MC.2023.3342602
中图分类号：
TP3 [计算技术、计算机技术];
学科分类号：
0812 ;
摘要：
Neural network (NN)-based network intrusion detection systems (NIDSs) are becoming popular these days due to their notable advantages. This article reviews the current application of explainable artificial intelligence techniques and tools for explaining the behavior of the NIDS.
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页码：78 / 85
页数：8
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