A cyber‐secure control‐detector architecture for nonlinear processes

doi:10.1002/aic.16907

This content will become publicly available on January 12, 2021

Title: A cyber‐secure control‐detector architecture for nonlinear processes

Authors:

Chen, Scarlett ^[1]; Wu, Zhe ^[1];

^[2]

Department of Chemical and Biomolecular EngineeringUniversity of California Los Angeles California
Department of Chemical and Biomolecular EngineeringUniversity of California Los Angeles California, Department of Electrical and Computer EngineeringUniversity of California Los Angeles California

Publication Date:: 2020-01-13

Sponsoring Org.:: USDOE

OSTI Identifier:: 1582486

Resource Type:: Publisher's Accepted Manuscript

Journal Name:: AIChE Journal

Additional Journal Information:: Journal Name: AIChE Journal; Journal ID: ISSN 0001-1541

Publisher:: Wiley Blackwell (John Wiley & Sons)

Country of Publication:: United States

Language:: English

Citation Formats


                    Chen, Scarlett, Wu, Zhe, and Christofides, Panagiotis D. A cyber‐secure control‐detector architecture for nonlinear processes.  United States: N. p., 2020. 
        Web.  doi:10.1002/aic.16907.

Copy to clipboard


                    Chen, Scarlett, Wu, Zhe, & Christofides, Panagiotis D. A cyber‐secure control‐detector architecture for nonlinear processes.  United States.  doi:10.1002/aic.16907.

Copy to clipboard


                    Chen, Scarlett, Wu, Zhe, and Christofides, Panagiotis D. Mon .  
        "A cyber‐secure control‐detector architecture for nonlinear processes".  United States.  doi:10.1002/aic.16907.

Copy to clipboard


                    
@article{osti_1582486,

  title        = {A cyber‐secure control‐detector architecture for nonlinear processes},

  author       = {Chen, Scarlett and Wu, Zhe and Christofides, Panagiotis D.},

  abstractNote = {},

  doi          = {10.1002/aic.16907},

  journal      = {AIChE Journal},

  number       = ,

  volume       = ,

  place        = {United States},

  year         = {2020},

  month        = {1}

}

Copy to clipboard

Journal Article:

Free Publicly Available Full Text

This content will become publicly available on January 12, 2021

Publisher's Version of Record

DOI: 10.1002/aic.16907

Other availability

Search WorldCat to find libraries that may hold this journal

Save / Share:

Export Metadata

Save to My Library

Works referenced in this record:

Attacks against process control systems: risk assessment, detection, and response
conference, January 2011

Cárdenas, Alvaro A.; Amin, Saurabh; Lin, Zong-Syun
Proceedings of the 6th ACM Symposium on Information, Computer and Communications Security - ASIACCS '11
DOI: 10.1145/1966913.1966959

Behaviour-Based Attack Detection and Classification in Cyber Physical Systems Using Machine Learning
conference, January 2016

Junejo, Khurum Nazir; Goh, Jonathan
Proceedings of the 2nd ACM International Workshop on Cyber-Physical System Security - CPSS '16
DOI: 10.1145/2899015.2899016

A Survey of Data Mining and Machine Learning Methods for Cyber Security Intrusion Detection
journal, July 2016

Buczak, Anna L.; Guven, Erhan
IEEE Communications Surveys & Tutorials, Vol. 18, Issue 2
DOI: 10.1109/COMST.2015.2494502

Bringing new technologies and approaches to the operation and control of chemical process systems
journal, March 2019

Rawlings, James B.; Maravelias, Christos T.
AIChE Journal, Vol. 65, Issue 6
DOI: 10.1002/aic.16615

Machine‐learning‐based predictive control of nonlinear processes. Part II: Computational implementation
journal, July 2019

Wu, Zhe; Tran, Anh; Rincon, David
AIChE Journal, Vol. 65, Issue 11
DOI: 10.1002/aic.16734

A Cumulative Sum-Based Fault Detector for Power System Relaying Application
journal, January 2008

Mohanty, S. R.; Pradhan, A. K.; Routray, A.
IEEE Transactions on Power Delivery, Vol. 23, Issue 1
DOI: 10.1109/TPWRD.2007.911160

Smart plant operations: Vision, progress and challenges
journal, January 2007

Christofides, Panagiotis D.; Davis, James F.; El-Farra, Nael H.
AIChE Journal, Vol. 53, Issue 11
DOI: 10.1002/aic.11320

Cooperative distributed model predictive control
journal, August 2010

Stewart, Brett T.; Venkat, Aswin N.; Rawlings, James B.
Systems & Control Letters, Vol. 59, Issue 8
DOI: 10.1016/j.sysconle.2010.06.005

Anomaly Detection in Cyber Physical Systems Using Recurrent Neural Networks
conference, January 2017

Goh, Jonathan; Adepu, Sridhar; Tan, Marcus
2017 IEEE 18th International Symposium on High Assurance Systems Engineering (HASE)
DOI: 10.1109/HASE.2017.36

Detecting and Handling Cyber-Attacks in Model Predictive Control of Chemical Processes
journal, September 2018

Wu, Zhe; Albalawi, Fahad; Zhang, Junfeng
Mathematics, Vol. 6, Issue 10
DOI: 10.3390/math6100173

Comprehensive study of decomposition effects on distributed output tracking of an integrated process over a wide operating range
journal, June 2018

Pourkargar, Davood Babaei; Almansoori, Ali; Daoutidis, Prodromos
Chemical Engineering Research and Design, Vol. 134
DOI: 10.1016/j.cherd.2018.04.045

Cybersecurity for Control Systems: A Process-Aware Perspective
journal, October 2016

Khorrami, Farshad; Krishnamurthy, Prashanth; Karri, Ramesh
IEEE Design & Test, Vol. 33, Issue 5
DOI: 10.1109/MDAT.2016.2594178

Modelling and optimization of a pilot-scale entrained-flow gasifier using artificial neural networks
journal, December 2019

Wang, Han; Chaffart, Donovan; Ricardez-Sandoval, Luis A.
Energy, Vol. 188
DOI: 10.1016/j.energy.2019.116076

Intrusion detection by machine learning: A review
journal, December 2009

Tsai, Chih-Fong; Hsu, Yu-Feng; Lin, Chia-Ying
Expert Systems with Applications, Vol. 36, Issue 10
DOI: 10.1016/j.eswa.2009.05.029

Subsystem decomposition of process networks for simultaneous distributed state estimation and control
journal, October 2018

Yin, Xunyuan; Liu, Jinfeng
AIChE Journal, Vol. 65, Issue 3
DOI: 10.1002/aic.16426

Nonlinear model predictive control of a multiscale thin film deposition process using artificial neural networks
journal, November 2019

Kimaev, Grigoriy; Ricardez-Sandoval, Luis A.
Chemical Engineering Science, Vol. 207
DOI: 10.1016/j.ces.2019.07.044

Model-based fault diagnosis in electric drives using machine learning
journal, June 2006

Yi Lu Murphey, ; Masrur, M. A.
IEEE/ASME Transactions on Mechatronics, Vol. 11, Issue 3
DOI: 10.1109/TMECH.2006.875568

Machine Learning Techniques for Anomaly Detection: An Overview
journal, October 2013

Omar, Salima; Ngadi, Asri; H. Jebur, Hamid
International Journal of Computer Applications, Vol. 79, Issue 2
DOI: 10.5120/13715-1478

Distributed moving horizon state estimation for nonlinear systems with bounded uncertainties
journal, October 2013

Zhang, Jing; Liu, Jinfeng
Journal of Process Control, Vol. 23, Issue 9
DOI: 10.1016/j.jprocont.2013.08.005

Survey on Anomaly Detection using Data Mining Techniques
journal, January 2015

Agrawal, Shikha; Agrawal, Jitendra
Procedia Computer Science, Vol. 60
DOI: 10.1016/j.procs.2015.08.220

Machine Learning Methods for Attack Detection in the Smart Grid
journal, August 2016

Ozay, Mete; Esnaola, Inaki; Yarman Vural, Fatos Tunay
IEEE Transactions on Neural Networks and Learning Systems, Vol. 27, Issue 8
DOI: 10.1109/TNNLS.2015.2404803

Optimization and control of a thin film growth process: A hybrid first principles/artificial neural network based multiscale modelling approach
journal, November 2018

Chaffart, Donovan; Ricardez-Sandoval, Luis A.
Computers & Chemical Engineering, Vol. 119
DOI: 10.1016/j.compchemeng.2018.08.029

Similar records in OSTI.GOV collections:

Towards a Standard for Highly Secure SCADA Systems

Conference Carlson, R.

The critical energy inkstructures include gas, OL and electric power. These Mrastructures are complex and interdependent nmvorks that are vital to the national secwiy and social well being of our nation. Many electric power systems depend upon gas and oil, while fossil energy delive~ systems depend upon elecnic power. The control mechanisms for these Mrastructures are often referred to as SCADA (Supmivry CkmdandDaU Ac@itz&z) systems. SCADA systems provide remote monitoring and centralized control for a distributed tmnsportation infmsmucture in order to facilitate delivery of a commodi~. AIthough many of the SCADA concepts developed in this paper can be applied tomore »« less
Full Text Available
Cyber Security Gap Analysis for Critical Energy Systems (CSGACES).

Technical Report Stamp, Jason E. ; Quiroz, Jimmy Edward ; Ellis, Abraham

This study describes a cyber security research & development (R&D) gap analysis and research plan to address cyber security for industrial control system (ICS) supporting critical energy systems (CES). The Sandia National Laboratories (SNL) team addressed a long-term perspective for the R&D planning and gap analysis. Investment will posture CES for sustained and resilient energy operations well into the future. Acknowledgements The authors would like to acknowledge the funding and technical support from the Department of Energy Office of Electricity Delivery & Energy Reliability for the development of this report. The authors are very appreciative of the key contributions bymore »« less
DOI: 10.2172/1494189

Full Text Available
A Scalable HPC Insider Threat Monitoring System

Technical Report Shevenell, Michael John

Cyber Equations, Inc. is reporting on the results of its DOE SBIR Phase I project for the development of a Scalable HPC Insider Threat Monitoring System. This final report to the Department of Energy for Task DE-FOA-0001618 covers the period from 02/21/2017 to 02/20/2018 and summarizes the larger research accomplishments, which can be divided in theoretical and laboratory experiments. One of the many challenges for the U.S. Department of Energy (DOE) is the support of the high‐performance computing (HPC) centers while providing quality information services, strategic vision, leadership, technical expertise, and capabilities necessary to enable the DOE to deliver effective,more »« less
DOI: 10.2172/1489161

Full Text Available
Microgrid cyber security reference architecture.

Technical Report Veitch, Cynthia K. ; Henry, Jordan M. ; Richardson, Bryan T. ; ...

This document describes a microgrid cyber security reference architecture. First, we present a high-level concept of operations for a microgrid, including operational modes, necessary power actors, and the communication protocols typically employed. We then describe our motivation for designing a secure microgrid; in particular, we provide general network and industrial control system (ICS)-speci c vulnerabilities, a threat model, information assurance compliance concerns, and design criteria for a microgrid control system network. Our design approach addresses these concerns by segmenting the microgrid control system network into enclaves, grouping enclaves into functional domains, and describing actor communication using data exchange attributes. Wemore »« less
DOI: 10.2172/1090210

Full Text Available
US-CERT Control System Center Input/Output (I/O) Conceputal Design

Technical Report Not Available

This document was prepared for the US-CERT Control Systems Center of the National Cyber Security Division (NCSD) of the Department of Homeland Security (DHS). DHS has been tasked under the Homeland Security Act of 2002 to coordinate the overall national effort to enhance the protection of the national critical infrastructure. Homeland Security Presidential Directive HSPD-7 directs the federal departments to identify and prioritize critical infrastructure and protect it from terrorist attack. The US-CERT National Strategy for Control Systems Security was prepared by the NCSD to address the control system security component addressed in the National Strategy to Secure Cyberspace andmore »« less
DOI: 10.2172/911878

Full Text Available

Similar Records

This content will become publicly available on January 12, 2021

Title: A cyber‐secure control‐detector architecture for nonlinear processes

Citation Formats

Attacks against process control systems: risk assessment, detection, and response conference, January 2011

Behaviour-Based Attack Detection and Classification in Cyber Physical Systems Using Machine Learning conference, January 2016

A Survey of Data Mining and Machine Learning Methods for Cyber Security Intrusion Detection journal, July 2016

Bringing new technologies and approaches to the operation and control of chemical process systems journal, March 2019

Machine‐learning‐based predictive control of nonlinear processes. Part II: Computational implementation journal, July 2019

A Cumulative Sum-Based Fault Detector for Power System Relaying Application journal, January 2008

Smart plant operations: Vision, progress and challenges journal, January 2007

Cooperative distributed model predictive control journal, August 2010

Anomaly Detection in Cyber Physical Systems Using Recurrent Neural Networks conference, January 2017

Detecting and Handling Cyber-Attacks in Model Predictive Control of Chemical Processes journal, September 2018

Comprehensive study of decomposition effects on distributed output tracking of an integrated process over a wide operating range journal, June 2018

Cybersecurity for Control Systems: A Process-Aware Perspective journal, October 2016

Modelling and optimization of a pilot-scale entrained-flow gasifier using artificial neural networks journal, December 2019

Intrusion detection by machine learning: A review journal, December 2009

Subsystem decomposition of process networks for simultaneous distributed state estimation and control journal, October 2018

Nonlinear model predictive control of a multiscale thin film deposition process using artificial neural networks journal, November 2019

Model-based fault diagnosis in electric drives using machine learning journal, June 2006

Machine Learning Techniques for Anomaly Detection: An Overview journal, October 2013

Distributed moving horizon state estimation for nonlinear systems with bounded uncertainties journal, October 2013

Survey on Anomaly Detection using Data Mining Techniques journal, January 2015

Machine Learning Methods for Attack Detection in the Smart Grid journal, August 2016

Optimization and control of a thin film growth process: A hybrid first principles/artificial neural network based multiscale modelling approach journal, November 2018

Attacks against process control systems: risk assessment, detection, and response
conference, January 2011

Behaviour-Based Attack Detection and Classification in Cyber Physical Systems Using Machine Learning
conference, January 2016

A Survey of Data Mining and Machine Learning Methods for Cyber Security Intrusion Detection
journal, July 2016

Bringing new technologies and approaches to the operation and control of chemical process systems
journal, March 2019

Machine‐learning‐based predictive control of nonlinear processes. Part II: Computational implementation
journal, July 2019

A Cumulative Sum-Based Fault Detector for Power System Relaying Application
journal, January 2008

Smart plant operations: Vision, progress and challenges
journal, January 2007

Cooperative distributed model predictive control
journal, August 2010

Anomaly Detection in Cyber Physical Systems Using Recurrent Neural Networks
conference, January 2017

Detecting and Handling Cyber-Attacks in Model Predictive Control of Chemical Processes
journal, September 2018

Comprehensive study of decomposition effects on distributed output tracking of an integrated process over a wide operating range
journal, June 2018

Cybersecurity for Control Systems: A Process-Aware Perspective
journal, October 2016

Modelling and optimization of a pilot-scale entrained-flow gasifier using artificial neural networks
journal, December 2019

Intrusion detection by machine learning: A review
journal, December 2009

Subsystem decomposition of process networks for simultaneous distributed state estimation and control
journal, October 2018

Nonlinear model predictive control of a multiscale thin film deposition process using artificial neural networks
journal, November 2019

Model-based fault diagnosis in electric drives using machine learning
journal, June 2006

Machine Learning Techniques for Anomaly Detection: An Overview
journal, October 2013

Distributed moving horizon state estimation for nonlinear systems with bounded uncertainties
journal, October 2013

Survey on Anomaly Detection using Data Mining Techniques
journal, January 2015

Machine Learning Methods for Attack Detection in the Smart Grid
journal, August 2016

Optimization and control of a thin film growth process: A hybrid first principles/artificial neural network based multiscale modelling approach
journal, November 2018