SS 07 - AI and Machine Learning for Safety and Security in Society 5.0

Special Session Organized by

Muhammad Taimoor Khan, School of Computing and Mathematical Sciences, University of Greenwich, UK and Dimitrios Serpanos, Industrial Systems Institute Athena, ECE University of Patras, Greece and Howard Shrobe, MIT CSAIL, USA and Kunio Uchiyama, National Institute of Advanced Industrial Science and Technology (AIST), Japan

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Computing constitutes a fundamental component of the emerging Society 5.0, which combines cyber and physical spaces (i.e., processes) and requires control and monitoring techniques for its operation and management. In Society 5.0, people, things, and systems are connected in cyberspace and operate exploiting automated methods, including machine learning (ML) and artificial intelligence (AI). Such operation and management bring new value to industry and society in ways not previously possible. Typical cyber physical systems (CPS) are based on (I)IoT (Industrial - Internet of Things) and (I)CPS (Industrial - Cyber Physical Systems) and have applications in all critical infrastructure domains with strict real-time requirements, such as healthcare, electric grid, transportation, to name a few. Intentional or accidental errors/failures/attacks to these systems have highly severe consequences. Therefore, novel design methodologies are required to ensure that design of real-time cyber physical systems and applications in the emerging Society 5.0 are free of vulnerabilities, threats and attacks. Since the physical part of CPS involves several processes, typically, it is challenging to ensure that the design is free from all known vulnerabilities. It is necessary to develop run-time monitoring and analysis techniques that can help to detect run-time incidents by observing the processes and their data. Furthermore, adequate modelling of CPS physical processes and corresponding cyber and physical attacks is fundamental to systematically model, analyze and verify real-time security of CPS. Importantly, since AI and machine learning have demonstrated their success in many application areas including cyber security, this special session focuses on investigating AI, machine learning and formal methods-based techniques to develop safe and secure real-time cyber physical systems at all levels, from hardware components to applications.

Topics under this session include (but not limited to)

  • AI and Machine Learning based
  • Safety and security of cyber-physical systems (CPS)
  • Prevention, detection and mitigation techniques for real-time CPS (RT-CPS) applications against cyber and physical threats
  • Hardware design for safe and secure RT-CPS
  • Vulnerability analysis of RT-CPS applications
  • False data injection attacks in RT-CPS applications
  • Performance analysis of RT-CPS security
  • RT-ICS network and communication security
  • Formal methods-based safety and security of critical systems at design-time and run-time
  • Safety and security of citizens in Society 5.0 including pandemics and disasters
  • Impact of pandemic and natural disasters on safety and security of citizens
  • CAD tools for AI-based cyber-physical systems (CPS)
  • CAD tools for safe and secure RT-CPS
  • Benchmarks for security and safety of RT-CPS
  • Challenges in modelling, analysis, safety and security of RT-CPS