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DESCRIPTION:Critical infrastructure control systems (CIS)\, such as energy\
 , transportation\, and manufacturing\, are expected to operate safely desp
 ite uncertain environments\, unexpected failures\, cyberattacks\, and AI-e
 nabled decision-making. Although modern control and verification technique
 s can provide safety guarantees\, these guarantees are only as reliable as
  the assumptions on which they are built. In this talk\, we focus on three
  questions: (1) How safe is a system when its environment deviates from th
 e assumptions used during design? (2) Can a system recover safe operation 
 after a disruption while continuing to function? (3) How can we leverage e
 merging AI technologies without sacrificing safety guarantees?\n\nTo addre
 ss these questions\, we use supervisory control theory of discrete-event s
 ystems to develop new methodologies for robustness analysis of controllers
 \, recovery strategy synthesis\, and AI-assisted decision verification. Th
 ese methodologies enable engineers to characterize safe operating envelope
 s of controllers\, identify realistic vulnerabilities\, design controllers
  that restore safe operation\, and formally validate AI-generated plans be
 fore deployment. We demonstrate how these methods enhance the safety and r
 esilience of CIS through case studies in manufacturing systems.\n\nRoom: 6
 2\, Bldg: Willard Building\, Penn State\, State College\, Pennsylvania\, U
 nited States\, 16802\, Virtual: https://events.vtools.ieee.org/m/577657
LOCATION:Room: 62\, Bldg: Willard Building\, Penn State\, State College\, P
 ennsylvania\, United States\, 16802\, Virtual: https://events.vtools.ieee.
 org/m/577657
ORGANIZER:manushankerbalasubramanian@gmail.com
SEQUENCE:12
SUMMARY:How Safe Is Safe Enough? Ensuring Safety and Resilience in Critical
  Infrastructure Control Systems
URL;VALUE=URI:https://events.vtools.ieee.org/m/577657
X-ALT-DESC:Description: <br /><p style="margin: 0in\; text-align: justify\;
 "><span style="font-family: 'Arial'\,sans-serif\; color: black\; mso-theme
 color: text1\;">Critical infrastructure control systems (CIS)\, such as en
 ergy\, transportation\, and manufacturing\, are expected to operate safely
  despite uncertain environments\, unexpected failures\, cyberattacks\, and
  AI-enabled decision-making. Although modern control and verification tech
 niques can provide safety guarantees\, these guarantees are only as reliab
 le as the assumptions on which they are built. In this talk\, we focus on 
 three questions: (1) How safe is a system when its environment deviates fr
 om the assumptions used during design? (2) Can a system recover safe opera
 tion after a disruption while continuing to function? (3) How can we lever
 age emerging AI technologies without sacrificing safety guarantees?</span>
 </p>\n<p style="margin: 0in\; text-align: justify\;">&nbsp\;</p>\n<p style
 ="margin: 0in\; text-align: justify\;"><span style="font-family: 'Arial'\,
 sans-serif\; color: black\; mso-themecolor: text1\;">To address these ques
 tions\, we use supervisory control theory of discrete-event systems to dev
 elop new methodologies for robustness analysis of controllers\, recovery s
 trategy synthesis\, and AI-assisted decision verification. These methodolo
 gies enable engineers to characterize safe operating envelopes of controll
 ers\, identify realistic vulnerabilities\, design controllers that restore
  safe operation\, and formally validate AI-generated plans before deployme
 nt. We demonstrate how these methods enhance the safety and resilience of 
 CIS through case studies in manufacturing systems.</span></p>
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