Detection and isolation of replay attacks through sensor watermarking

Riccardo M.G. Ferrari, A.M. Herdeiro Teixeira

Research output: Chapter in Book/Conference proceedings/Edited volumeConference contributionScientificpeer-review

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Abstract

This paper addresses the detection and isolation of replay attacks on sensor measurements. As opposed to previously proposed additive watermarking, we propose a multiplicative watermarking scheme, where each sensor's output is separately watermarked by being fed to a SISO watermark generator. Additionally, a set of equalizing filters is placed at the controller's side, which reconstructs the original output signals from the received watermarked data. We show that the proposed scheme has several advantages over existing approaches: it has no detrimental effects on the closed-loop performance in the absence of attacks; it can be designed in a modular fashion, independently of the design of the controller and anomaly detector; it facilitates the detection of replay attacks and the isolation of the time at which the replayed data was recorded. These properties are discussed in detail and the results are illustrated through a numerical example.

Original languageEnglish
Title of host publicationIFAC-PapersOnLine
Subtitle of host publicationProceedings 20th IFAC World Congress
EditorsD Dochian, D Henrion, D Peaucelle
Place of PublicationLaxenburg, Austria
PublisherElsevier
Pages7363-7368
Volume50-1
DOIs
Publication statusPublished - 2017
Event20th World Congress of the International Federation of Automatic Control (IFAC), 2017 - Toulouse, France
Duration: 9 Jul 201714 Jul 2017
Conference number: 20
https://www.ifac2017.org

Publication series

NameIFAC-PapersOnLine
PublisherIFAC-Elsevier
Number1
Volume50
ISSN (Print)2405-8963

Conference

Conference20th World Congress of the International Federation of Automatic Control (IFAC), 2017
Abbreviated titleIFAC 2017
Country/TerritoryFrance
CityToulouse
Period9/07/1714/07/17
Internet address

Keywords

  • Channel equalisation
  • Control over networks
  • diagnosis
  • Fault detection

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