Detecting Industrial Control Malware Using Automated PLC Code Analytics
- 1 November 2014
- journal article
- Published by Institute of Electrical and Electronics Engineers (IEEE) in IEEE Security & Privacy
- Vol. 12 (6), 40-47
- https://doi.org/10.1109/msp.2014.113
Abstract
The authors discuss their research on programmable logic controller (PLC) code analytics, which leverages safety engineering to detect and characterize PLC infections that target physical destruction of power plants. Their approach also draws on control theory, namely the field of engineering and mathematics that deals with the behavior of dynamical systems, to reverse-engineer safety-critical code to identify complex and highly dynamic safety properties for use in the hybrid code analytics approach.Keywords
This publication has 8 references indexed in Scilit:
- A Trusted Safety Verifier for Process Controller CodePublished by Internet Society ,2014
- SABOTPublished by Association for Computing Machinery (ACM) ,2012
- Anomaly detection via statistical learning in industrial communication networksInternational Journal of Information and Computer Security, 2011
- RRE: A game-theoretic intrusion Response and Recovery EnginePublished by Institute of Electrical and Electronics Engineers (IEEE) ,2009
- Secure Control: Towards Survivable Cyber-Physical SystemsPublished by Institute of Electrical and Electronics Engineers (IEEE) ,2008
- BitBlaze: A New Approach to Computer Security via Binary AnalysisLecture Notes in Computer Science, 2008
- Using symbolic execution for verifying safety-critical systemsACM SIGSOFT Software Engineering Notes, 2001
- Automatic symbolic verification of embedded systemsIEEE Transactions on Software Engineering, 1996