Journal
IEEE TRANSACTIONS ON DEPENDABLE AND SECURE COMPUTING
Volume 13, Issue 1, Pages 133-145Publisher
IEEE COMPUTER SOC
DOI: 10.1109/TDSC.2015.2415489
Keywords
Plug-in electric vehicles; learning automata; Bayesian coalition negotiation game; authentication
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In recent times, Plug-in Electric Vehicles (PEVs) have emerged as a new alternative to increase the efficiency of smart grids (SGs) in a vehicles-to-grid (V2G) environment. The V2G environment provides a bidirectional power and information flow, so that users can have an optimized usage as per their requirements. However, uncontrolled and unmanaged power distribution may lead to an overall performance degradation in V2G environment. One reason for this uncontrolled and unmanaged flow may be due to the usage of power by unauthorized users. To address this issue, we propose a Bayesian Coalition Negotiation Game (BCNG) as a utility for secure energy management for PEVs in the V2G environment. We have used a BCNG along with Learning Automata (LA), wherein LA are stationed on PEVs and are assumed as the players in the game. To provide an approach based on resilience for any misuse of electricity consumption, a new Secure Payoff Function (SPF) is proposed. The players take actions and update their action probability vector using the SPF. A Nash Equilibrium (NE) is also achieved in the game using convergence theory. Our proposal is evaluated with various metrics. The proposed scheme also provides mutual authentication and resilience against various attacks during power distribution.
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