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Numrering	Referens	Omslagsbild	Hitta
1.	Lin, Chih-Yuan, 1987-, et al. (författare) Timing-Based Anomaly Detection in SCADA Networks 2018 Ingår i: Critical Information Infrastructures Security. - Cham : Springer. - 9783319998428 - 9783319998435 ; , s. 48-59 Konferensbidrag (refereegranskat)abstract Supervisory Control and Data Acquisition (SCADA) systems that operate our critical infrastructures are subject to increased cyber attacks. Due to the use of request-response communication in polling, SCADA traffic exhibits stable and predictable communication patterns. This paper provides a timing-based anomaly detection system that uses the statistical attributes of the communication patterns. This system is validated with three datasets, one generated from real devices and two from emulated networks, and is shown to have a False Positive Rate (FPR) under 1.4%. The tests are performed in the context of three different attack scenarios, which involve valid messages so they cannot be detected by whitelisting mechanisms. The detection accuracy and timing performance are adequate for all the attack scenarios in request-response communications. With other interaction patterns (i.e. spontaneous communications), we found instead that 2 out of 3 attacks are detected.

Lin, Chih-Yuan, 1987-, et al. (författare)
Timing-Based Anomaly Detection in SCADA Networks
2018
Ingår i: Critical Information Infrastructures Security. - Cham : Springer. - 9783319998428 - 9783319998435 ; , s. 48-59
Konferensbidrag (refereegranskat)abstract
- Supervisory Control and Data Acquisition (SCADA) systems that operate our critical infrastructures are subject to increased cyber attacks. Due to the use of request-response communication in polling, SCADA traffic exhibits stable and predictable communication patterns. This paper provides a timing-based anomaly detection system that uses the statistical attributes of the communication patterns. This system is validated with three datasets, one generated from real devices and two from emulated networks, and is shown to have a False Positive Rate (FPR) under 1.4%. The tests are performed in the context of three different attack scenarios, which involve valid messages so they cannot be detected by whitelisting mechanisms. The detection accuracy and timing performance are adequate for all the attack scenarios in request-response communications. With other interaction patterns (i.e. spontaneous communications), we found instead that 2 out of 3 attacks are detected.

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