I-Corps: An Investigation of the Commercial Potential of Cyber-physical Security for Advanced Manufacturing Systems

Virginia Polytechnic Institute And State University, Blacksburg VA

Investigators

Abstract

The broader impact/commercial potential of this I-Corps project will provide the manufacturing industry with an approach to identify and detect cyber-physical attacks within their production environments in real-time. Currently, the manufacturing industry is operating production systems vulnerable to malicious attacks, which may cause produced parts to not meet intended design requirements. Such a deviation from design intent could result in damaged products, loss of customer trust, and potentially injure employees and/or customers. The adoption of the proposed approach will secure manufacturers from cyber-physical attacks and create a strong supply chain. This will allow manufacturers to continue to produce sensitive parts both for the general public and the defense industry, increasing the difficulty of a malicious attack to affect part production. Through successful completion of this program, the I-Corps team will further develop awareness in this area through mentoring graduate students and discussing cyber-physical security with manufacturers across the United States. This I-Corps project employs both traditional decision analysis and data analysis techniques to identify and detect malicious events within manufacturing systems. This is done through a two-phase approach. First, a cyber-physical vulnerability assessment is completed which highlights areas within the production environment susceptible to malicious attack. Employing decision trees and process mapping, the vulnerability assessment is used to provide a high level overview of the cyber-physical resiliency of a manufacturing facility. Second, the proposed detection approach consists of an air-gapped sensor suite which can be placed on any piece of critical equipment to detect malicious events in real-time. The proposed approach analyzes side-channel measurements independent of the machine such as power consumption, vibration, and sound to identify anomalies within the process. Through performing the vulnerability assessment and implementing the proposed sensor suite, the entire production facility can be secured from malicious cyber-physical attacks intended to reduce part quality and/or sabotage produced parts. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.