SACSys - Safe and Secure Adaptive Collaborative Systems

Status:

active

Start date:

2019-09-01

End date:

2023-08-31

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.

[Show all publications]

Priority Based Ethernet Handling in Real-Time End System with Ethernet Controller Filtering (Oct 2022)
Bjarne Johansson, Mats Rågberger , Thomas Nolte, Alessandro Papadopoulos
48th Annual Conference of the Industrial Electronics Society (IECON 2022)

Cyberattacks: Modeling, Analysis, and Mitigation (Sep 2022)
Sara Abbaspour
6th International Conference on Computer, Software and Modeling (ICCSM)

TOLERANCER: A Fault Tolerance Approach for Cloud Manufacturing Environments (Sep 2022)
Auday Al-Dulaimy, Christian Sicari , Alessandro Papadopoulos, Antonino Galletta , Massimo Villari , Mohammad Ashjaei
International Conference on Emerging Technologies and Factory (ETFA'2022)

POSTER: Towards Cyber Resilience of Cyber-Physical Systems using Tiny Twins (Aug 2022)
Fereidoun Moradi, Sara Abbaspour, Marjan Sirjani
7th IEEE European Symposium on Security and Privacy (EuroS&P 2022)

Monitoring Cyber-Physical Systems Using a Tiny Twin to Prevent Cyber-Attacks (Aug 2022)
Fereidoun Moradi, Maryam Bagheri , Hanieh Rahmati , Hamed Yazdi , Sara Abbaspour, Marjan Sirjani
25TH INTERNATIONAL CONFERENCE ON FORMAL METHODS FOR INDUSTRIAL CRITICAL SYSTEMS (FMICS)

Kubernetes Orchestration of High Availability Distributed Control Systems (Aug 2022)
Bjarne Johansson, Mats Rågberger , Thomas Nolte, Alessandro Papadopoulos
23rd IEEE International Conference on Industrial Technology (ICIT 2022)

PartnerType
ABB Robotics Industrial
Volvo Cars Industrial
Volvo Construction Equipment AB Industrial
Volvo GTO Industrial

Marjan Sirjani, Professor

Email: marjan.sirjani@mdh.se
Room: U1-066C
Phone: +46736620517