Intrusion Detection in Water Distribution Systems using Machine Learning Techniques: A Survey

被引：1
|
作者：
Mabunda, Hlayisani D. [1 ]
Ramotsoela, Daniel T. [1 ]
Abu-Mahfouz, Adnan M. [2 ]
机构：
[1] Univ Cape Town, Dept Elect Engn, Cape Town, South Africa
[2] Council Sci & Ind Res CSIR, Pretoria, South Africa
来源：
2022 IEEE 31ST INTERNATIONAL SYMPOSIUM ON INDUSTRIAL ELECTRONICS (ISIE) | 2022年
关键词：
Water distribution systems; cyber-physical systems; machine learning;
D O I：
10.1109/ISIE51582.2022.9831687
中图分类号：
T [工业技术];
学科分类号：
08 ;
摘要：
Water distribution systems (WDS) are designed to supply potable water to businesses, industries and people in any area or location. Cyber-Physical systems (CPS) are used in water distribution systems and come with aided benefits, however, these systems are exposed to intruders who attack these systems for their own personal gain or to sabotage the system. There are a number of different techniques which are available to stop intruders from penetrating these systems and this paper discussed different machine learning tehniques that can detect anomalies and as a result stop any potential intrusion.
引用
收藏
页码：418 / 423
页数：6
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