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Title: A Bernoulli Gaussian Watermark for Detecting Integrity Attacks in Control Systems

Abstract

We examine the merit of Bernoulli packet drops in actively detecting integrity attacks on control systems. The aim is to detect an adversary who delivers fake sensor measurements to a system operator in order to conceal their effect on the plant. Physical watermarks, or noisy additive Gaussian inputs, have been previously used to detect several classes of integrity attacks in control systems. In this paper, we consider the analysis and design of Gaussian physical watermarks in the presence of packet drops at the control input. On one hand, this enables analysis in a more general network setting. On the other hand, we observe that in certain cases, Bernoulli packet drops can improve detection performance relative to a purely Gaussian watermark. This motivates the joint design of a Bernoulli-Gaussian watermark which incorporates both an additive Gaussian input and a Bernoulli drop process. We characterize the effect of such a watermark on system performance as well as attack detectability in two separate design scenarios. Here, we consider a correlation detector for attack recognition. We then propose efficiently solvable optimization problems to intelligently select parameters of the Gaussian input and the Bernoulli drop process while addressing security and performance trade-offs. Finally, we providemore » numerical results which illustrate that a watermark with packet drops can indeed outperform a Gaussian watermark.« less

Authors:
 [1];  [1];  [1]
  1. Carnegie Mellon Univ., Pittsburgh, PA (United States)
Publication Date:
Research Org.:
Carnegie Mellon University
Sponsoring Org.:
USDOE Office of Electricity Delivery and Energy Reliability (OE)
OSTI Identifier:
1406344
DOE Contract Number:  
OE0000779
Resource Type:
Conference
Resource Relation:
Conference: 55. Annual Allerton Conference on Communication, Control, and Computing, Monticello, IL (United States), 27-30 Sep 2017
Country of Publication:
United States
Language:
English
Subject:
32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATION

Citation Formats

Weerakkody, Sean, Ozel, Omur, and Sinopoli, Bruno. A Bernoulli Gaussian Watermark for Detecting Integrity Attacks in Control Systems. United States: N. p., 2017. Web. doi:10.1109/ALLERTON.2017.8262842.
Weerakkody, Sean, Ozel, Omur, & Sinopoli, Bruno. A Bernoulli Gaussian Watermark for Detecting Integrity Attacks in Control Systems. United States. doi:10.1109/ALLERTON.2017.8262842.
Weerakkody, Sean, Ozel, Omur, and Sinopoli, Bruno. Thu . "A Bernoulli Gaussian Watermark for Detecting Integrity Attacks in Control Systems". United States. doi:10.1109/ALLERTON.2017.8262842. https://www.osti.gov/servlets/purl/1406344.
@article{osti_1406344,
title = {A Bernoulli Gaussian Watermark for Detecting Integrity Attacks in Control Systems},
author = {Weerakkody, Sean and Ozel, Omur and Sinopoli, Bruno},
abstractNote = {We examine the merit of Bernoulli packet drops in actively detecting integrity attacks on control systems. The aim is to detect an adversary who delivers fake sensor measurements to a system operator in order to conceal their effect on the plant. Physical watermarks, or noisy additive Gaussian inputs, have been previously used to detect several classes of integrity attacks in control systems. In this paper, we consider the analysis and design of Gaussian physical watermarks in the presence of packet drops at the control input. On one hand, this enables analysis in a more general network setting. On the other hand, we observe that in certain cases, Bernoulli packet drops can improve detection performance relative to a purely Gaussian watermark. This motivates the joint design of a Bernoulli-Gaussian watermark which incorporates both an additive Gaussian input and a Bernoulli drop process. We characterize the effect of such a watermark on system performance as well as attack detectability in two separate design scenarios. Here, we consider a correlation detector for attack recognition. We then propose efficiently solvable optimization problems to intelligently select parameters of the Gaussian input and the Bernoulli drop process while addressing security and performance trade-offs. Finally, we provide numerical results which illustrate that a watermark with packet drops can indeed outperform a Gaussian watermark.},
doi = {10.1109/ALLERTON.2017.8262842},
journal = {},
number = ,
volume = ,
place = {United States},
year = {2017},
month = {11}
}

Conference:
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