Behavioral Switching in CPS Security: Challenges and Opportunities

We highlight the emergence of hybrid phenomena in security applications involving cyber-physical systems. Leveraging results from differential games, we apply online deterministic annealing on a space of potential attacking behaviors that can inform the defender of the system about both the different types of attackers on the environment and their distribution. We further showcase how the complexity of switching on dynamical systems can be employed as a defensive tool on its own merit. Towards this, we develop a probabilistic switching feedback control mechanism that deceives an adversarial identifier. Our studies underscore the plethora of opportunities that hybrid system methods present for security analysts and defense experts in cyber-physical systems; as detection approaches as well as design techniques.

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Published
2025-06-24
DOI
https://doi.org/10.23919/ecc65951.2025.11186849
Primary Topic
Advanced Malware Detection Techniques
Type
article
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article

Behavioral Switching in CPS Security: Challenges and Opportunities

Aris Kanellopoulos
Advanced Malware Detection Techniques
article

Behavioral Switching in CPS Security: Challenges and Opportunities

Aris Kanellopoulos
article en

Abstract

We highlight the emergence of hybrid phenomena in security applications involving cyber-physical systems. Leveraging results from differential games, we apply online deterministic annealing on a space of potential attacking behaviors that can inform the defender of the system about both the different types of attackers on the environment and their distribution. We further showcase how the complexity of switching on dynamical systems can be employed as a defensive tool on its own merit. Towards this, we develop a probabilistic switching feedback control mechanism that deceives an adversarial identifier. Our studies underscore the plethora of opportunities that hybrid system methods present for security analysts and defense experts in cyber-physical systems; as detection approaches as well as design techniques.

KTH Royal Institute of Technology (SE)
Openalex Percentile: Top 64%
Advanced Malware Detection Techniques
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