Exploring malicious meter inspection in neighborhood area smart grids

Zhifeng Xiao, Yang Xiao, David Hung Chang Du

Research output: Contribution to journalArticle

65 Scopus citations

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.

Original languageEnglish (US)
Article number6397580
Pages (from-to)214-226
Number of pages13
JournalIEEE Transactions on Smart Grid
Volume4
Issue number1
DOIs
StatePublished - Jan 4 2013

Keywords

  • Accountability
  • advanced metering infrastructure (AMI)
  • attack
  • malicious meter inspection
  • security
  • smart grid
  • smart meter

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