Security of cyberphysical systems quantified through age of information

Cyber-physical systems (CPS) play essential roles in modern infrastructure and enable real-time monitoring and control of a wide variety of applications such as healthcare, transportation, and energy. The integration of physical and cyber components into CPS introduces consid- erable security challenges, including adversary induced false data injection attacks. Given the substantial impact of security compromises on swimmingly emerging, often offered systems; it is vital to protect CPS from the reality if becoming vulnerable to attacks. A key aspect of performance and security of CPS is the ”freshness” of the information passed onto the deci- sion maker, or controller. Freshness is often provided by the notion of the Age of Information (AoI) metric that computes the elapsed time from when the last received update was created. AoI impacts the ability of the CPS to react to anything happening in real-time and respond with resilience while under adversarial conditions. The thesis investigates the role of AoI as a metric that describes security involved in protecting CPS. Using a game-theoretic framework, the research examines strategic interactions between a controller seeking to minimize AoI and an adversary attempt to maximize disruption through false data injection. By simulating vari- ous attack scenarios—including jamming and update disruption—and implementing adaptive scheduling strategies, the study identifies optimal responses that minimize AoI despite adver- sarial interference. The study extends existing AoI models by incorporating factors such as natural process drift, transmission costs, and adversarial behavior, offering a comprehensive view of how information latency affects system resilience. Generally, the thesis points to AoI as a high sensitivity and reliability indicator of security performance; significantly under con- strained resources and strategy threats. The research produces an application of more resilient CPS while combining scheduling with protection and adaptively navigating update decisions and strategic engagement. The research provides a new direction for assessing security in real- time and opens new ideas for future work in a multi-agent defense, adaptability via learning, and physical deployment in smart environments. This thesis explores the role of AoI as a metric for assessing and improving security in CPS. Using a game-theoretic framework, the research examines strategic interactions between a controller seeking to minimize AoI and an adversary attempt to maximize disruption through false data injection. The study extends existing AoI models by incorporating factors such as natural process drift, transmission costs, and adversarial behavior, offering a comprehensive view of how information latency affects system resilience. The analysis also considers the interplay between update frequency and the cost-effectiveness of security measures, emphasizing proactive monitoring and optimization strategies. Through simulations and theoretical analysis, this work aims to provide actionable insights into enhancing CPS resilience, offering a quantitative foundation for designing secure, efficient, and responsive systems.