There is a rapid development of technology such as self-driving cars and collaborating robots. These products are additionally integrated into collaborating ensembles, capable of delivering collaborative functions, such as vehicle platooning. At the same time as the complexity and diversity of these systems grow, they have to become increasingly adaptive, both because their complex interplay and behavior cannot be fully predicted and analyzed at design-time, and also because they operate in unpredictable environments. Current state-of practice in system architecture, software development and safety and security assurance is challenged by this development.
In SACSys, we address the core question of how to provide run-time guarantees of safety and cyber-security for time-critical collaborative adaptive systems. For achieving this goal, we will recognize and define continuous safety and security requirements with time-criticality features in adaptive systems (through subproject CASSA), and design behavioral models at run-time to analyze and check conformance of the safety and security requirements (through subproject APAC). The analysis of such models will be executed in a suitable cloud-based platform with real-time guarantees, provided by novel approaches (developed within subproject RTCloud). These subprojects will each contribute with a required element, and jointly provide a viable answer to the SACSys core question. The Swedish industrial giants, Volvo Cars, Volvo GTO, Volvo CE and ABB Robotics participate in coproduction throughout the project by provision of requirements and use cases as well as involvement and guidance in research focus and implementation. The co-production and results of SACSys are expected to increase the business prospects of the industrial partners by increased competence and key solutions that will strengthen their competitiveness related to design of collaborative adaptive system products and services. Prof. Edward Lee from UC Berkeley, the world’s leading expert in cyber-physical systems, and Prof. David Garlan from CMU, the internationally known expert in self-adaptive software, will contribute as external advisors of the project.
|Associated Senior Lecturer
|Associated Senior Lecturer
Tiny Twins for detecting cyber-attacks at runtime using concise Rebeca time transition (Feb 2024) Fereidoun Moradi, Bahman Pourvatan , Sara Abbaspour, Marjan Sirjani Journal of Parallel and Distributed Computing (JPDC 185)
Assessing Risk of AR and Organizational Changes Factors in Socio-technical Robotic Manufacturing (Jan 2024) Soheila Sheikh Bahaei, Barbara Gallina Journal of Robotics and Computer-Integrated Manufacturing, Vol.88, 102731 (RCIM-2024)
Selective Trimmed Average: A Resilient Federated Learning Algorithm With Deterministic Guarantees on the Optimality Approximation (Jan 2024) Mojtaba Kaheni, Martina Lippi , Andrea Gasparri , Mauro Franceschelli IEEE Transactions on Cybernetics (IEEE TCyb)
Hierarchical Resource Orchestration Framework for Real-Time Containers (Jan 2024) Václav Struhár, Silviu Craciunas , Mohammad Ashjaei, Moris Behnam, Alessandro Papadopoulos ACM Transactions on Embedded Computing Systems (TECS 2024)
From TARA to Test: Automated Automotive Cybersecurity Test Generation Out of Threat Modeling (Dec 2023) Stefan Marksteiner, Christoph Schmittner , Korbinian Christl , Dejan Nickovic , Mikael Sjödin, Marjan Sirjani 7th ACM Computer Science in Cars Symposium (CSCS'23)