On Using Physical Based Intrusion Detection in SCADA Systems

被引:17
作者
Al-Asiri, Majed [1 ]
El-Alfy, El-Sayed M. [1 ]
机构
[1] King Fahd Univ Petr & Minerals, Dhahran 31261, Saudi Arabia
来源
11TH INTERNATIONAL CONFERENCE ON AMBIENT SYSTEMS, NETWORKS AND TECHNOLOGIES (ANT) / THE 3RD INTERNATIONAL CONFERENCE ON EMERGING DATA AND INDUSTRY 4.0 (EDI40) / AFFILIATED WORKSHOPS | 2020年 / 170卷
关键词
Information Security; SCADA; Industrial Control Systems; Cyber Physical Systems (CPS); Industrial Internet of Things (IIoT); Intrusion Detection; Taxonomy; SECURITY;
D O I
10.1016/j.procs.2020.03.007
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
Intrusion detection in SCADA systems has received increased attention from researchers as connectivity to public networks became a necessity in many industries. The nature and characteristics of SCADA systems call for special considerations and techniques of intrusion detection. Many works have been made in this field, ranging from generic intrusion detection techniques to customized solutions designed specifically for SCADA systems. In the recent years, some works have focused on using physical metrics in addition to the popular network-based and host-based intrusion detection approaches. This paper presents a taxonomy that considers the special features of cyberphysical intrusion detection systems (IDSs) with examples from the literature. Moreover, a case study is presented for a simulated gas pipeline dataset to compare the effectiveness of decision tree classifiers for various categories of features in SCADA systems. The results show that an IDS that uses a combination of physical and network metrics significantly outperforms an IDS that only uses network metrics or physical metrics. (C) 2020 The Authors. Published by Elsevier B.V.
引用
收藏
页码:34 / 42
页数:9
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