Security of Cyber-Physical Systems in the Presence of Transient Sensor Faults
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Published:2017-07-24
Issue:3
Volume:1
Page:1-23
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ISSN:2378-962X
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Container-title:ACM Transactions on Cyber-Physical Systems
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language:en
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Short-container-title:ACM Trans. Cyber-Phys. Syst.
Author:
Park Junkil1,
Ivanov Radoslav1,
Weimer James1,
Pajic Miroslav2,
Son Sang Hyuk3,
Lee Insup1
Affiliation:
1. University of Pennsylvania, Philadelphia, PA
2. Duke University, Durham, NC
3. Daegu Gyeongbuk Institute of Science and Technology, Daegu, Korea
Abstract
This article is concerned with the security of modern Cyber-Physical Systems in the presence of transient sensor faults. We consider a system with multiple sensors measuring the same physical variable, where each sensor provides an interval with all possible values of the true state. We note that some sensors might output faulty readings and others may be controlled by a malicious attacker. Differing from previous works, in this article, we aim to distinguish between faults and attacks and develop an attack detection algorithm for the latter only. To do this, we note that there are two kinds of faults—transient and permanent; the former are benign and short-lived, whereas the latter may have dangerous consequences on system performance. We argue that sensors have an underlying transient fault model that quantifies the amount of time in which transient faults can occur. In addition, we provide a framework for developing such a model if it is not provided by manufacturers.
Attacks can manifest as either transient or permanent faults depending on the attacker’s goal. We provide different techniques for handling each kind. For the former, we analyze the worst-case performance of sensor fusion over time given each sensor’s transient fault model and develop a filtered fusion interval that is guaranteed to contain the true value and is bounded in size. To deal with attacks that do not comply with sensors’ transient fault models, we propose a sound attack detection algorithm based on pairwise inconsistencies between sensor measurements. Finally, we provide a real-data case study on an unmanned ground vehicle to evaluate the various aspects of this article.
Funder
NSF
NRF and the DGIST Research and Development Program
DARPA
ONR
Intel-NSF Partnership for Cyber-Physical Systems Security and Privacy
Global Research Laboratory Program
Ministry of Science, ICT 8 Future Planning
Publisher
Association for Computing Machinery (ACM)
Subject
Artificial Intelligence,Control and Optimization,Computer Networks and Communications,Hardware and Architecture,Human-Computer Interaction
Reference47 articles.
1. An Approach for Detecting and Distinguishing Errors versus Attacks in Sensor Networks
2. Michèle Basseville Igor V. Nikiforov and others. 1993. Detection of Abrupt Changes: Theory and Application. Vol. 104. Prentice Hall Englewood Cliffs NJ. Michèle Basseville Igor V. Nikiforov and others. 1993. Detection of Abrupt Changes: Theory and Application. Vol. 104. Prentice Hall Englewood Cliffs NJ.
3. Black-I. Robotics. 2015. LandShark UGV. Retrieved from http://blackirobotics.com/LandShark_UGV_UC0M.html. Black-I. Robotics. 2015. LandShark UGV. Retrieved from http://blackirobotics.com/LandShark_UGV_UC0M.html.
4. Robust distributed computing and sensing algorithm
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