Introducing randomness into univariate control chart sampling strategies for enhancing security against cyber‐physical attacks in production systems

Abstract

AbstractWith recent technological advancements, production systems have become more susceptible to cyber‐physical attacks. Such attacks can be intelligently designed to both alter product dimensions and avoid detection by current Quality Control (QC) tools. The objective of this work is to assess the performance of random sampling strategies for control charting in detecting cyber‐physical attacks. More specifically, the methodology adopts traditional random sampling approaches used for inspection and applies them to univariate control charts. Different random sampling strategies are discussed and their performances under varying attack scenarios are evaluated. In addition, new control chart performance metrics were developed for a more in‐depth analysis, to guide practitioners in assessing how well these control charts increase their robustness to cyber‐physical attacks.