Look-Up Table based FHE System for Privacy Preserving Anomaly Detection in Smart Grids

Ruixiao Li, Shameek Bhattacharjee, Sajal K. Das, Hayato Yamana

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

In advanced metering infrastructure (AMI), the customers' power consumption data is considered private but needs to be revealed to data-driven attack detection frameworks. In this paper, we present a system for privacy-preserving anomaly-based data falsification attack detection over fully homomorphic encrypted (FHE) data, which enables computations required for the attack detection over encrypted individual customer smart meter's data. Specifically, we propose a homomorphic look-up table (LUT) based FHE approach that supports privacy preserving anomaly detection between the utility, customer, and multiple partied providing security services. In the LUTs, the data pairs of input and output values for each function required by the anomaly detection framework are stored to enable arbitrary arithmetic calculations over FHE. Furthermore, we adopt a private information retrieval (PIR) approach with FHE to enable approximate search with LUTs, which reduces the execution time of the attack detection service while protecting private information. Besides, we show that by adjusting the significant digits of inputs and outputs in our LUT, we can control the detection accuracy and execution time of the attack detection, even while using FHE. Our experiments confirmed that our proposed method is able to detect the injection of false power consumption in the range of 11-17 secs of execution time, depending on detection accuracy.

Original languageEnglish
Title of host publicationProceedings - 2022 IEEE International Conference on Smart Computing, SMARTCOMP 2022
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages108-115
Number of pages8
ISBN (Electronic)9781665481526
DOIs
Publication statusPublished - 2022
Event8th IEEE International Conference on Smart Computing, SMARTCOMP 2022 - Espoo, Finland
Duration: 2022 Jun 202022 Jun 24

Publication series

NameProceedings - 2022 IEEE International Conference on Smart Computing, SMARTCOMP 2022

Conference

Conference8th IEEE International Conference on Smart Computing, SMARTCOMP 2022
Country/TerritoryFinland
CityEspoo
Period22/6/2022/6/24

Keywords

  • FHE
  • anomaly (attack) detection
  • look-up table
  • privacy-preserving
  • smart grid

ASJC Scopus subject areas

  • Artificial Intelligence
  • Computer Science Applications
  • Computer Vision and Pattern Recognition

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