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Detection of Control Injection Attacks using Energy Data Anomalies in CNC Machining

by Curtis R Taylor, Jeffrey C Kimmell, Vladimir Orlyanchik, Logan D Sturm, Joel A Dawson
Publication Type
Conference Paper
Book Title
International Conference on Critical Infrastructure Protection
Publication Date
Page Numbers
1 to 28
Conference Name
Eighteenth Annual IFIP WG 11.10 International Conference on Critical Infrastructure Protection
Conference Location
Arlington, Virginia, United States of America
Conference Sponsor
IFIP WG 11.10
Conference Date

The widespread adoption of networked devices, sophisticated automation, and data-driven processes in the industry - also known as Industry 4.0 - has boosted the quantity and quality of manufacturing products. With these benefits, however, comes a substantial increase in the attack surface of these systems. In addition to affecting the readiness and the quality of critical products, the attacks against manufacturing processes and systems carry the potential to have severe physical consequences, including human injury and death. In this paper we present the results of a remote network-based control injection attack on a CNC mill. Specifically, we focus on the impact of this type of the attack on the movement of CNC mill during operation. Evaluating the physical effect of these attacks on a workpiece, we provide machine agnostic, affordable, and scalable solution for their monitoring. We then demonstrate a simple threshold-based method for the detection of these attacks and evaluate the effectiveness of detection.