Interdependence-Aware Game-Theoretic Framework for Secure Intelligent Transportation Systems

• Published in: IEEE internet of things journal 2021-11, Vol.8 (22), p.16395-16405
• Main Authors: Ferdowsi, Aidin, Eldosouky, Abdelrahman, Saad, Walid
• Format: Article
• Language: English
• Subjects: Base stations; Communications infrastructure (CI); Critical infrastructure; Electric power grids; Energy consumption; Failure; Game theory; Games; Infrastructure; Intelligent transportation systems; intelligent transportation systems (ITSs); interdependence; Internet of Things; Power grids; power grids (PGs); Power sources; Risk allocation; Security; Stackelberg equilibrium (SE); Streets; Traffic congestion; Traffic flow; Traffic jams
• ISSN: 2327-4662; 2327-4662
• DOI: 10.1109/JIOT.2020.3020899

The operation of future intelligent transportation systems (ITSs), communications infrastructure (CI), and power grids (PGs) will be highly interdependent. In particular, autonomous connected vehicles require CI resources to operate, and, thus, communication failures can result in nonoptimality in the ITS flow in terms of traffic jams and fuel consumption. Similarly, CI components, e.g., base stations (BSs) can be impacted by failures in the electric grid that is powering them. Thus, malicious attacks on the PG can lead to failures in both the CI and the ITSs. To this end, in this article, the security of an ITS against indirect attacks carried out through the PG is studied in an interdependent PG-CI-ITS scenario. In the considered scenario, an attacker can induce nonoptimality in the ITS or disrupt a particular set of streets by attacking the PG components while remaining stealthy from the ITS administrators. To defend against such attacks, the administrator of the interdependent critical infrastructure can allocate backup power sources (BPSs) at every BS to compensate for the power loss caused by the attacker. However, due to budget limitations, the administrator must consider the importance of each BS in light of the PG risk of failure, while allocating the BPSs. In this regard, a rigorous analytical framework is proposed to model the interdependencies between the ITS, CI, and PG. Next, a one-to-one relationship between the PG components and ITS streets is derived in order to capture the effect of the PG components' failure on the optimality of the traffic flow in the streets. Moreover, the problem of BPS allocation is formulated using a Stackelberg game framework and the Stackelberg equilibrium (SE) of the game is characterized. Simulation results show that the derived SE outperforms any other BPS allocation strategy and can be scalable in linear time with respect to the size of the interdependent infrastructure.