A Survey of Cyber-Physical Systems From a Game-Theoretic Perspective

Abstract

With the emergence of the Internet-of-Things (IoT), artificial intelligence, and communication technologies, cyber-physical systems (CPS) have revolutionized the engineering paradigm with profound applications in many aspects of society including homes, energy, agriculture, health-care, transportation, business, and manufacturing. A CPS uses suitable computational techniques such as game theory to enable different entities to interact with one another for taking necessary actions to obtain selected objectives. Recent literature on CPS has extensively used game theory to approach a variety of technical challenges. In order to make these contributions more accessible to a broader audience, there is a need for studies that can provide readers with a comprehensive understanding of different types of CPS and their attributes, then clearly outline why game theory is relevant for modeling different aspects of CPS, and also discuss how game theory has been used in relevant literature to date. This paper bridges this gap by 1) providing a general discussion of different types of CPS and their characteristics; 2) giving an overview of different types of game-theoretic approaches; 3) explaining why game theory is appropriate for modeling different types of CPS; and 4) finally, studying how game theory has been used in different CPS types to address their challenges. Further, we also identify some key research challenges for future investigation where game theory could be applied as a potential solution.

FlipDyn: A game of resource takeovers in dynamical systems

“…The FlipDyn game with control of dynamical system -FlipDyn-Con, is completely defined by the expected cost (7) and the space of player takeover strategies and control input policies subject to the dynamics in (4) and (3). In the next section, we derive the outcome of the FlipDyn game with control for both the FlipDyn state of α = 0 and α = 1 for general systems.…”

“…For a finite cardinality of the state X , fixed player policies u k and w k , k ∈ K, and a finite horizon L, Theorem 1 yields an exact saddle-point value of the FlipDyn-Con game (7). However, the computational and storage complexities scale undesirably with the cardinality of X , especially in continuous state spaces.…”

“…Recursions (81) and (84) provide an approximate solution to the FlipDyn-Con problem (7) for the n-dimensional case with corresponding takeover and control policies. Similar to the range of the parameter η k presented in Lemma 1, the parameters η k and η k under a mixed strategy NE takeover can be bounded using condition (36), indicated in the following remark.…”

“…However, alongside the benefits of these advancements, there has also been a notable surge in adversarial activities, wherein malicious actors exploit the connectivity between the cyber and physical parts of the system [4]- [6], resulting in potential damages and vulnerabilities. To fortify CPS against these vulnerabilities, novel paradigms are emerging at the intersection of game theory [7], control theory [6], and machine learning [8], paving the way for strategic defense mechanisms.…”

A UAV-Assisted Stackelberg Game Model for Securing loMT Healthcare Networks

“…Furthermore, our proposed scheme provokes the SEE technique to recover the resource in case it is hacked. Game theory [20] is a mathematical framework widely used to analyze strategic interactions between multiple decision-makers, where each decision's outcome depends on others' decisions [21,22]. In the context of UAVs, game theory is an efficient technique for modelling and analyzing the interactions between multiple UAVs, UAVs, and ground-based agents and between numerous ground-based agents coordinating with UAVs [23].…”