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Securing Manufacturing Industrial Control Systems: Behavioral Anomaly Detection



Michael P. Powell, James J. McCarthy, CheeYee Tang, Keith Stouffer, Timothy Zimmerman, William C. Barker, Titilayo Ogunyale, Devin M. Wynne


Industrial control systems (ICS) are used in many industries to monitor and control physical processes. As ICS continue to adopt commercially available information technology (IT) to promote corporate business systems' connectivity and remote access capabilities, ICS become more vulnerable to cybersecurity threats. The National Institute of Standards and Technology's (NIST's) National Cybersecurity Center of Excellence (NCCoE), in conjunction with NIST's Engineering Laboratory (EL), has demonstrated a set of behavioral anomaly detection capabilities to support cybersecurity in manufacturing organizations. These capabilities enable manufacturers to detect anomalous conditions in their operating environments to mitigate malware attacks and other threats to the integrity of critical operational data. NIST's NCCoE and EL have mapped these demonstrated capabilities to the Cybersecurity Framework and have documented how this set of standards-based controls can support many of the security requirements of manufacturers. This report documents the use of behavioral anomaly detection (BAD) capabilities in two distinct but related demonstration environments: a robotics-based manufacturing system and a process control system that resembles what is being used by chemical manufacturing industries.
NIST Interagency/Internal Report (NISTIR) - 8219
Report Number


BAD, behavioral anomaly detection, cybersecurity, Cybersecurity Framework, ICS, industrial control systems, manufacturing, process control


Powell, M. , McCarthy, J. , Tang, C. , Stouffer, K. , Zimmerman, T. , Barker, W. , Ogunyale, T. and Wynne, D. (2020), Securing Manufacturing Industrial Control Systems: Behavioral Anomaly Detection, NIST Interagency/Internal Report (NISTIR), National Institute of Standards and Technology, Gaithersburg, MD, [online], (Accessed May 29, 2024)


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Created July 15, 2020, Updated March 1, 2021