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Title: Active Detection for Exposing Intelligent Attacks in Control Systems

Abstract

In this paper, we consider approaches for detecting integrity attacks carried out by intelligent and resourceful adversaries in control systems. Passive detection techniques are often incorporated to identify malicious behavior. Here, the defender utilizes finely-tuned algorithms to process information and make a binary decision, whether the system is healthy or under attack. We demonstrate that passive detection can be ineffective against adversaries with model knowledge and access to a set of input/output channels. We then propose active detection as a tool to detect attacks. In active detection, the defender leverages degrees of freedom he has in the system to detect the adversary. Specifically, the defender will introduce a physical secret kept hidden from the adversary, which can be utilized to authenticate the dynamics. In this regard, we carefully review two approaches for active detection: physical watermarking at the control input, and a moving target approach for generating system dynamics. We examine practical considerations for implementing these technologies and discuss future research directions.

Authors:
 [1];  [1];  [1];  [1]
  1. Carnegie Mellon Univ., Pittsburgh, PA (United States)
Publication Date:
Research Org.:
Carnegie Mellon Univ., Pittsburgh, PA (United States)
Sponsoring Org.:
USDOE Office of Electricity Delivery and Energy Reliability (OE)
OSTI Identifier:
1373581
DOE Contract Number:  
OE0000779
Resource Type:
Conference
Resource Relation:
Conference: 1st IEEE Conference on Control Technology and Applications , Kohala Coast (Hawaii), 27-30 Aug 2017
Country of Publication:
United States
Language:
English
Subject:
25 ENERGY STORAGE; 29 ENERGY PLANNING, POLICY, AND ECONOMY

Citation Formats

Weerakkody, Sean, Ozel, Omur, Griffioen, Paul, and Sinopoli, Bruno. Active Detection for Exposing Intelligent Attacks in Control Systems. United States: N. p., 2017. Web. doi:10.1109/CCTA.2017.8062639.
Weerakkody, Sean, Ozel, Omur, Griffioen, Paul, & Sinopoli, Bruno. Active Detection for Exposing Intelligent Attacks in Control Systems. United States. doi:10.1109/CCTA.2017.8062639.
Weerakkody, Sean, Ozel, Omur, Griffioen, Paul, and Sinopoli, Bruno. Sat . "Active Detection for Exposing Intelligent Attacks in Control Systems". United States. doi:10.1109/CCTA.2017.8062639. https://www.osti.gov/servlets/purl/1373581.
@article{osti_1373581,
title = {Active Detection for Exposing Intelligent Attacks in Control Systems},
author = {Weerakkody, Sean and Ozel, Omur and Griffioen, Paul and Sinopoli, Bruno},
abstractNote = {In this paper, we consider approaches for detecting integrity attacks carried out by intelligent and resourceful adversaries in control systems. Passive detection techniques are often incorporated to identify malicious behavior. Here, the defender utilizes finely-tuned algorithms to process information and make a binary decision, whether the system is healthy or under attack. We demonstrate that passive detection can be ineffective against adversaries with model knowledge and access to a set of input/output channels. We then propose active detection as a tool to detect attacks. In active detection, the defender leverages degrees of freedom he has in the system to detect the adversary. Specifically, the defender will introduce a physical secret kept hidden from the adversary, which can be utilized to authenticate the dynamics. In this regard, we carefully review two approaches for active detection: physical watermarking at the control input, and a moving target approach for generating system dynamics. We examine practical considerations for implementing these technologies and discuss future research directions.},
doi = {10.1109/CCTA.2017.8062639},
journal = {},
number = ,
volume = ,
place = {United States},
year = {Sat Jul 01 00:00:00 EDT 2017},
month = {Sat Jul 01 00:00:00 EDT 2017}
}

Conference:
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