Exploring Malicious Meter Inspection in Neighborhood Area Smart Grids

Abstract

In smart grids, smart meters may potentially be attacked or compromised to cause certain security risks. It is challenging to identify malicious meters when there are a large number of users. In this paper, we explore the malicious meter inspection (MMI) problem in neighborhood area smart grids. We propose a suite of inspection algorithms in a progressive manner. First, we present a basic scanning method, which takes linear time to accomplish inspection. The scanning method is efficient when the malicious meter ratio is high. Then, we propose a binary-tree-based inspection algorithm, which performs better than scanning when the malicious meter ratio is low. Finally, we employ an adaptive-tree-based algorithm, which leverages advantages of both the scanning and binary-tree inspections. Our approaches are tailored to fit both static and dynamic situations. The theoretical and experimental results have shown the effectiveness of the adaptive tree approach.