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Title: A Covert System Identification Attack on Constant Setpoint Control Systems

Abstract

Industrial Control Systems (ICS) are the brain and backbone of nation’s critical infrastructure such as nuclear power, water treatment, and petrochemical plants. In order to increase interoperability, real-time availability of data, and flexibility, information/communication technologies are adopted in this domain. While these information technologies have been effective, they are integrated into operational technologies without the necessary security defense. Designing an effective, layered security defense is not possible unless security threats are identified through a structural analysis of the ICS. For that reason, this paper provides an attacker’s point of view on the reconnaissance effort necessary to gather details ofthe system dynamics - which are required for the development of sophisticated attacks. We present a reconnaissance approach which uses the system’s I/O data to infer the dynamic model of the system. In this effort, we propose a novel cyber-attack which targets the controller proportional-integral-derivative gain values in a constant setpoint control system. Our findings will help researchers design more secure control systems.

Authors:
 [1];  [2];  [2]; ORCiD logo [3]
  1. Boise State Univsersity
  2. Boise State University
  3. Idaho National Laboratory
Publication Date:
Research Org.:
Idaho National Lab. (INL), Idaho Falls, ID (United States)
Sponsoring Org.:
Boise State University
OSTI Identifier:
1599057
Report Number(s):
INL/CON-19-54494-Rev001
DOE Contract Number:  
DE-AC07-05ID14517
Resource Type:
Conference
Resource Relation:
Conference: WICS'19 - 6th International Workshop on Information and Communication Security - Part of CANDAR'19, Nagasaki, Japan, 11/26/2019 - 11/29/2019
Country of Publication:
United States
Language:
English
Subject:
97 - MATHEMATICS AND COMPUTING; cybersecurity; control systems; system identification; covert attack

Citation Formats

Phillips, Tyler, Mehrpouyan, Hoda, Gardner, John, and Reese, Stephen J. A Covert System Identification Attack on Constant Setpoint Control Systems. United States: N. p., 2020. Web. doi:10.1109/CANDARW.2019.00070.
Phillips, Tyler, Mehrpouyan, Hoda, Gardner, John, & Reese, Stephen J. A Covert System Identification Attack on Constant Setpoint Control Systems. United States. doi:10.1109/CANDARW.2019.00070.
Phillips, Tyler, Mehrpouyan, Hoda, Gardner, John, and Reese, Stephen J. Mon . "A Covert System Identification Attack on Constant Setpoint Control Systems". United States. doi:10.1109/CANDARW.2019.00070. https://www.osti.gov/servlets/purl/1599057.
@article{osti_1599057,
title = {A Covert System Identification Attack on Constant Setpoint Control Systems},
author = {Phillips, Tyler and Mehrpouyan, Hoda and Gardner, John and Reese, Stephen J},
abstractNote = {Industrial Control Systems (ICS) are the brain and backbone of nation’s critical infrastructure such as nuclear power, water treatment, and petrochemical plants. In order to increase interoperability, real-time availability of data, and flexibility, information/communication technologies are adopted in this domain. While these information technologies have been effective, they are integrated into operational technologies without the necessary security defense. Designing an effective, layered security defense is not possible unless security threats are identified through a structural analysis of the ICS. For that reason, this paper provides an attacker’s point of view on the reconnaissance effort necessary to gather details ofthe system dynamics - which are required for the development of sophisticated attacks. We present a reconnaissance approach which uses the system’s I/O data to infer the dynamic model of the system. In this effort, we propose a novel cyber-attack which targets the controller proportional-integral-derivative gain values in a constant setpoint control system. Our findings will help researchers design more secure control systems.},
doi = {10.1109/CANDARW.2019.00070},
journal = {},
number = ,
volume = ,
place = {United States},
year = {2020},
month = {1}
}

Conference:
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