Value Of Intrusion Detection Systems For Countering Energy Fraud

The large-scale deployment of smart meters has spurred innovations in customer analytics and network inspection tools. In this article, we focus on the practical question faced by many electricity distribution utilities: How to assess the value of these technological tools in limiting nontechnical losses, specifically energy diversion? We present a Bayesian inspection game that models the interaction between a profit-maximizing distribution utility and a population of strategic customers. A fraction of customer population is fraudulent and can choose to conduct energy diversion attacks by under-reporting their energy consumption. The distribution utility can tune (or configure) an intrusion detection system (IDS) to achieve an "optimal" tradeoff between the detection and false alarm rates. Our analysis provides a way to estimate value of IDS products to a monopolist distribution utility in a regulatory environment with a fixed tariff schedule for all customers and fine (penalty) to the fraudulent customers whose energy diversions are successfully investigated. We analyze how the value of IDS varies with the fraction of fraudulent customers and the extent to which they under-report their consumption.