Skip to main content
U.S. Department of Energy
Office of Scientific and Technical Information

A Bernoulli Gaussian Watermark for Detecting Integrity Attacks in Control Systems

Conference ·
 [1];  [2];  [2]
  1. Carnegie Mellon Univ., Pittsburgh, PA (United States); University of Arkansas
  2. Carnegie Mellon Univ., Pittsburgh, PA (United States)
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.
Research Organization:
Carnegie Mellon University
Sponsoring Organization:
USDOE Office of Electricity Delivery and Energy Reliability (OE)
DOE Contract Number:
OE0000779
OSTI ID:
1406344
Country of Publication:
United States
Language:
English

Similar Records

Physical Watermarking for Securing Cyber-Physical Systems via Packet Drop Injections
Conference · Mon Oct 23 00:00:00 EDT 2017 · OSTI ID:1406349

Joint attack detection and secure state estimation of cyber‐physical systems
Journal Article · Wed Aug 28 20:00:00 EDT 2019 · International Journal of Robust and Nonlinear Control · OSTI ID:1564494

Active Detection for Exposing Intelligent Attacks in Control Systems
Conference · Sat Jul 01 00:00:00 EDT 2017 · OSTI ID:1373581