Exploration of For-Purpose Decentralized Algorithmic Cyber Attacks in EV Charging Control

Abstract

Distributed and decentralized multi-agent optimization (DMAO) algorithms enable the control of large-scale grid-edge resources, such as electric vehicles (EV), to provide power grid services. Despite its great scalability, DMAO is fundamentally prone to cyber attacks as it is highly dependent on frequent peer-to-peer communications. Existing cyber-security research in this regard mainly focuses on \emph{broad-spectrum} attacks aiming at jeopardizing the entire control system while losing the possibility of achieving specific attacking purposes. This paper, for the first time, explores novel \emph{for-purpose} algorithmic attacks that are launched by participating agents and interface with DMAO to achieve self-interest attack purposes. A decentralized EV charging control problem is formulated as an illustrative use case. Theoretical \emph{for-purpose} attack vectors with and without the stealthy feature are devised. Simulations on EV charging control show the practicability of the proposed algorithmic \emph{for-purpose} attacks and the impacts of such attacks on distribution networks.