DRACE: A Framework for Evaluating Anomaly Detectors for Industrial Control Systems

被引：0

作者：

Christian, Ivan ^{[1
]}

Furtado, Francisco ^{[1
]}

Mathur, Aditya P. ^{[1
]}

机构：

[1] SUTD, ITrust, Singapore, Singapore

来源：

PROCEEDINGS OF THE 10TH ACM CYBER-PHYSICAL SYSTEM SECURITY WORKSHOP, ACM CPSS 2024 | 2024年

基金：

新加坡国家研究基金会;

关键词：

Anomaly detection; Cyber exercise; Industrial Control Systems; Cyber Security; Performance Metrics; Critical Infrastructure; Tools;

D O I：

10.1145/3626205.3659145

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

The detection of process anomalies is a critical step in defending a physical plant against cyber-attacks. We propose a framework named DRACE that includes a set of metrics to evaluate the effectiveness of anomaly detectors, referred to as Intrusion Detection Systems (IDS). Different from those used in the literature, the proposed metrics are designed to serve as a means for plant engineers and IT specialists to compare multiple detectors prior to deciding which to deploy. The metrics were found effective in evaluating the effectiveness of several anomaly detectors of different origins in a case study conducted in the iTrust laboratory.

引用

页码：77 / 87

页数：11

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