TY - JOUR
T1 - SURE
T2 - A modeling and simulation integration platform for evaluation of SecUre and REsilient cyber-physical systems
AU - Koutsoukos, Xenofon
AU - Karsai, Gabor
AU - Laszka, Aron
AU - Neema, Himanshu
AU - Potteiger, Bradley
AU - Volgyesi, Peter
AU - Vorobeychik, Yevgeniy
AU - Sztipanovits, Janos
N1 - Funding Information:
Manuscript received May 8, 2017; revised July 17, 2017; accepted July 17, 2017. Date of publication August 15, 2017; date of current version December 20, 2017. This work was supported by the Air Force Research Laboratory under Award FA 8750-14-2-0180 and by the National Science Foundation under Grant CNS-1238959. Any opinions, findings, and conclusions or recommendations expressed in this material are those of the author(s) and do not necessarily reflect the views of the Air Force Research Laboratory or the National Science Foundation. (Corresponding author: Xenofon Koutsoukos.) The authors are with the Institute for Software Integrated Systems, Vanderbilt University, Nashville, TN 37212 USA (e-mail: xenofon.koutsoukos@vanderbilt.edu; gabor.karsai@vanderbilt.edu; aron.laszka@vanderbilt.edu; himanshu.neema@ vanderbilt.edu; peter.volgyesi@vanderbilt.edu; yevgeniy.vorobeychik@vanderbilt.edu; janos.sztipanovits@vanderbilt.edu).
Publisher Copyright:
© 2017 IEEE.
PY - 2018/1
Y1 - 2018/1
N2 - The exponential growth of information and communication technologies have caused a profound shift in the way humans engineer systems leading to the emergence of closedloop systems involving strong integration and coordination of physical and cyber components, often referred to as cyber-physical systems (CPSs). Because of these disruptive changes, physical systems can now be attacked through cyberspace and cyberspace can be attacked through physical means. The paper considers security and resilience as system properties emerging from the intersection of system dynamics and the computing architecture. A modeling and simulation integration platform for experimentation and evaluation of resilient CPSs is presented using smart transportation systems as the application domain. Evaluation of resilience is based on attacker-defender games using simulations of sufficient fidelity. The platform integrates 1) realistic models of cyber and physical components and their interactions; 2) cyber attack models that focus on the impact of attacks to CPS behavior and operation; and 3) operational scenarios that can be used for evaluation of cybersecurity risks. Three case studies are presented to demonstrate the advantages of the platform: 1) vulnerability analysis of transportation networks to traffic signal tampering; 2) resilient sensor selection for forecasting traffic flow; and 3) resilient traffic signal control in the presence of denial-of-service attacks.
AB - The exponential growth of information and communication technologies have caused a profound shift in the way humans engineer systems leading to the emergence of closedloop systems involving strong integration and coordination of physical and cyber components, often referred to as cyber-physical systems (CPSs). Because of these disruptive changes, physical systems can now be attacked through cyberspace and cyberspace can be attacked through physical means. The paper considers security and resilience as system properties emerging from the intersection of system dynamics and the computing architecture. A modeling and simulation integration platform for experimentation and evaluation of resilient CPSs is presented using smart transportation systems as the application domain. Evaluation of resilience is based on attacker-defender games using simulations of sufficient fidelity. The platform integrates 1) realistic models of cyber and physical components and their interactions; 2) cyber attack models that focus on the impact of attacks to CPS behavior and operation; and 3) operational scenarios that can be used for evaluation of cybersecurity risks. Three case studies are presented to demonstrate the advantages of the platform: 1) vulnerability analysis of transportation networks to traffic signal tampering; 2) resilient sensor selection for forecasting traffic flow; and 3) resilient traffic signal control in the presence of denial-of-service attacks.
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U2 - 10.1109/JPROC.2017.2731741
DO - 10.1109/JPROC.2017.2731741
M3 - Article
AN - SCOPUS:85028448058
SN - 0018-9219
VL - 106
SP - 93
EP - 112
JO - Proceedings of the Institute of Radio Engineers
JF - Proceedings of the Institute of Radio Engineers
IS - 1
ER -