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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.