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    On Remote State Estimation in the Presence of an Eavesdropper


    Leong, Enoch, Quevedo, Daniel E., Dolz, Daniel and Dey, Subhrakanti (2017) On Remote State Estimation in the Presence of an Eavesdropper. IFAC-PapersOnLine, 50 (1). pp. 7339-7344. ISSN 2405-8963

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    Abstract

    This paper studies a remote state estimation problem in the presence of an eavesdropper. A sensor transmits local state estimates over a packet dropping link to a remote estimator, which at the same time can be overheard by an eavesdropper with a certain probability. The objective is to determine when the sensor should transmit, in order to minimize the estimation error covariance at the remote estimator, while trying to keep the eavesdropper error covariance above a certain level. This is done by solving an optimization problem that minimizes a linear combination of the expected estimation error covariance and the negative of the expected eavesdropper error covariance. Structural results on the optimal transmission policy are derived, and shown to exhibit thresholding behaviour in the estimation error covariances. In the infinite horizon situation, it is shown that with unstable systems one can keep the expected estimation error covariance bounded while the expected eavesdropper error covariance becomes unbounded.
    Item Type: Article
    Additional Information: This paper was presented at IFAC 2017 World Congress - The 20th World Congress of the International Federation of Automatic Control, 9-14 Jul 2017, Toulouse, France.
    Keywords: Embedded systems; State estimation; Sensor attacks;
    Academic Unit: Faculty of Science and Engineering > Electronic Engineering
    Faculty of Science and Engineering > Research Institutes > Hamilton Institute
    Item ID: 11899
    Identification Number: 10.1016/j.ifacol.2017.08.1482
    Depositing User: Subhrakanti Dey
    Date Deposited: 28 Nov 2019 12:05
    Journal or Publication Title: IFAC-PapersOnLine
    Publisher: Elsevier
    Refereed: Yes
    Related URLs:
    URI: https://mural.maynoothuniversity.ie/id/eprint/11899
    Use Licence: This item is available under a Creative Commons Attribution Non Commercial Share Alike Licence (CC BY-NC-SA). Details of this licence are available here

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