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Cyber and Physical Anomaly Detection in Smart-Grids

  • Daniel L. Marino
  • , Chathurika S. Wickramasinghe
  • , Kasun Amarasinghe
  • , Hari Challa
  • , Philip Richardson
  • , Ananth A. Jillepalli
  • , Brian K. Johnson
  • , Craig Rieger
  • , Milos Manic

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

35 Scopus citations

Abstract

The inclusion of Information and Communication Technologies (ICTs) in industrial control systems (ICSs) has opened ICSs to several attack vectors, which are increasingly targeting critical infrastructure. Accurate detection and distinction between benign physical disturbances, malicious cyber-attacks, and malicious physical-attacks are necessary to protect critical infrastructure. While cyber sensors provide a useful tool to identify and mitigate cyber attacks, they often ignore the physical behavior of the system at hand. In this paper, we present a cyber-physical sensor called IREST (ICS Resilient Security Technology). The sensor takes a holistic approach in detecting anomalies by considering both cyber and physical disturbances in a complex system. The sensor was tested under different cyber-physical scenarios using the Idaho CPS SCADA Cybersecurity (ISAAC) testbed. The test scenarios capture different operational states of the CPS testbed, including various cyber and physical anomalies. The experiments show that the IREST sensor is able to detect both cyber and physical anomalies. The sensor has the benefit that training requires only normal data and is able to detect disturbances that have not been seen before. The presented approach provides a scalable framework for cyber-physical security research that can be expanded in the future.

Original languageEnglish
Title of host publicationProceedings - 2019 Resilience Week, RWS 2019
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages187-193
Number of pages7
ISBN (Electronic)9781728121352
DOIs
StatePublished - Nov 2019
Event2019 Resilience Week, RWS 2019 - San Antonio, United States
Duration: Nov 4 2019 → Nov 7 2019

Publication series

NameProceedings - 2019 Resilience Week, RWS 2019

Conference

Conference2019 Resilience Week, RWS 2019
Country/TerritoryUnited States
CitySan Antonio
Period11/4/19 → 11/7/19

Keywords

  • Anomaly Detection
  • Cyber-physical systems
  • Machine Learning
  • SCADA

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