NFD: Non-technical loss fraud detection in Smart Grid

Abstract

Utility companies consistently suffer from the harassing of Non-Technical Loss (NTL) frauds globally. In the traditional power grid, electricity theft is the main form of NTL frauds. In Smart Grid, smart meters thwart electricity theft in some ways but cause more problems, e.g., intrusions, hacking, and malicious manipulation. Various detectors have been proposed to detect NTL frauds, but they either rely on user behavior analysis which requires a large amount of historical data or needs a lot of extra devices which are expensive. In this paper, a detector, named NFD (NTL Fraud Detection), is proposed to detect NTL frauds with only a small amount of data and one additional device. NFD is based on Lagrange polynomial interpolation to model an adversary's behaviors, and detect a tampered meter by comparing the difference between the results. Different from existing detectors, our detector knows adversaries better than adversaries themselves. By building mathematical models of these adversaries, we can predict their behaviors which they may not be aware of by themselves. NFD makes it practical to detect NTL frauds both online and offline in Smart Grid. NFD can facilitate real-world applications before Smart Grid is fully deployed since it can serve the traditional power grid and Smart Grid simultaneously. Experimental results show the effectiveness of NFD. It can detect multiple tampered meters and multiple adversaries, as well as a single tampered meter and a single adversary. We also study how to tune the parameters used in NFD to further guide its practical usage.

Smart Grid Metering Networks: A Survey on Security, Privacy and Open Research Issues

“…An energy theft (by means of a meter compromise) is usually referred to as non-technical loss to the utility company [114]. An attacker can make such theft by meter bypassing, meter compromising and tampering, and/or defective meters.…”

“…Mitigation to smart meter compromise: An attacker can compromise the smart meter to make energy theft. More precisely, the energy companies are approximately losing millions of dollars annually due to energy theft [114].…”

“…Based on the mathematical analysis, Han-Xiao proposed a non-technical loss fraud detection (NFD) [114]. The NFD utilized Lagrange polynomial interpolation model to detect the behaviour of multiple compromised meters and multiple adversaries.…”

“…For instance, in a real-time scenario where each meter may have different accuracy at different timings. Moreover, the scheme proposed in [114] requires additional observer meters, which may add significant deployment and maintenance costs to the utility companies. Similarly, Yip et al proposed another mathematical model to detect defective smart meters and energy theft in [153].…”

“…Summary: Table XI summarizes the mitigations to smart meter cloning [152], [113]; meter compromise [114], [154]; and meter location migration [156], [115], including their communication mode, involved entities, test-bed/simulation, security and privacy goals, and description with pros and cons. Each scheme is proposed to be a safeguard to theft of services in smart grid.…”