A Testing Based Approach for Security Analysis of Smart Semiconductor Systems.

Winter Simulation Conference(2023)

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Abstract
Digital factories have been recognized as a paradigm with considerable promise for improving manufacturing performance. Digital Twins have emerged as a powerful tool to improve control performance for large-scale smart manufacturing systems. We argue that DT-based smart factories are vulnerable to attacks that use the DT to damage the system while remaining undetectable, specifically in high-cost processes, where DT technologies are more likely to be deployed. As an instructive example, we look into smart semiconductor processes with focus on photolithography. To this end, we formulate a static optimization problem to maximize the damage of a cyber-attack against a photolithography digital twin that minimizes detectability to the process controller. Results demonstrate that this problem formulation provides attack policies that successfully reduce the throughput of the system at trade off of increased detectability to a common process control technique. Results encourage more research in the domain, especially to face scalability and policy-like solutions.
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Key words
Optimal State,Manufacturing Systems,Static Problem,System Throughput,Considerable Promise,Smart Manufacturing,Digital Twin,System State,Evolutionary Algorithms,Cycle Time,Manufacturing Industry,Additive Manufacturing,Number Of Tools,Anomaly Detection,Semiconductor Industry,Frequency Of Attacks,Cyber-physical Systems,Lot Number,Layered System,Reticle,Control Chart,Photolithography Process,Previous Attack,Blockchain,Threat Model,Industrial Internet Of Things,Rate Of Anomalies,Brute Force,Physical System
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