ASM2S Project

Automated Synthesis of Runtime Monitors for Safe & Secure Distributed Industrial Systems

The goal of the project is to develop methods and tools for the automated synthesis of runtime security monitors for distributed applications of industrial processes. The monitor will detect computational and false data injection attacks, combining verification techniques for computational attacks and fault diagnosis techniques for dynamic systems in order to detect false data injection attacks. The objectives are (1) the development of behavior‐based methods for detecting deviations of a distributed application execution from the specified behavior of a correct application specification, (2) the development of fault detection and diagnosis methods for false data injection attacks in distributed industrial applications, (3) the development of a unified monitoring methodology that combines the above methods, and (4) the development of a method and a tool the automatically synthesizes a monitor using the unified monitoring framework.

The "Automated Synthesis of Runtime Monitors for Safe & Secure Distributed Industrial Systems" (ASM2S) project has been awarded funding under the 2nd Call for H.F.R.I.'s Research Projects to Support Faculty Members & Researchers.

Our Team

Committed to knowledge, driven by impact

Dimitrios Serpanos

Industrial Systems Institute, Athena RC, Greece

Christos Koulamas

Industrial Systems Institute, Athena RC, Greece

George E. Raptis

Industrial Systems Institute, Athena RC, Greece

Spilios D. Fassois

SMSA Lab, University of Patras, Greece

John S. Sakellariou

SMSA Lab, University of Patras, Greece

Ilias A. Iliopoulos

SMSA Lab, University of Patras, Greece

Ioannis E. Saramantas

SMSA Lab, University of Patras, Greece

Sabby Cohen

SMSA Lab, University of Patras, Greece

Muhammad Taimoor Khan

Cyber Assurance Lab, University of Greenwich, UK

Howard Shrobe

Massachusetts Institute of Technology, USA

Marilyn Wolf

University of Nebraska-Lincoln, USA

Publications

Advancing knowledge, inspiring change

G. E. Raptis, M. T. Khan, C. Koulamas, and D. Serpanos, "Applying Inline Monitoring to Detect Run-Time Security Incidents in Water Distribution Systems", 2024 IEEE 50th 50th Annual Conference of the IEEE Industrial Electronics Society (IECON), Nov. 3-6, 2024.

G. E. Raptis, M. T. Khan, C. Koulamas, and D. Serpanos, "Towards Integration of EPANET and ASM2S To Enhance Security in Water Distribution Systems", 2024 IEEE 29th International Conference on Emerging Technologies and Factory Automation (ETFA), vol. 32. IEEE, pp. 01–08, Sep. 10, 2024. doi: 10.1109/etfa61755.2024.10710978

I. E. Saramantas, J. S. Sakellariou, S. D. Fassois, I. A. Iliopoulos, and D. Serpanos, "Sensor fault detection and identification for robust SHM in a population of composite aerostructures under varying excitation and temperature", 2024 International Conference on Noise and Vibration Engineering (ISMA), Sep. 9-11, 2024.

D. Serpanos and G. Xenos, "Vertical Federated Learning in Malware Detection for Smart Cities", 2023 IEEE International Smart Cities Conference (ISC2). IEEE, pp. 1–5, Sep. 24, 2023. doi: 10.1109/isc257844.2023.10293429.

D. Serpanos and G. Xenos, “Federated Learning in Malware Detection,” 2023 IEEE 28th International Conference on Emerging Technologies and Factory Automation (ETFA). IEEE, pp. 1–4, Sep. 12, 2023. doi: 10.1109/etfa54631.2023.10275578.

G. E. Raptis, M. T. Khan, K. Stefanidis, C. Koulamas, and D. Serpanos, "Towards Run-Time Security Monitoring of Distributed Industrial Control Systems", 2023 IEEE 28th International Conference on Emerging Technologies and Factory Automation (ETFA). IEEE, pp. 1–8, Sep. 12, 2023. doi: 10.1109/etfa54631.2023.10275618.

D. Serpanos, "False Data Injection Attacks on Sensor Systems", Proceedings of the 41st IEEE/ACM International Conference on Computer-Aided Design. ACM, pp. 1–5, Oct. 30, 2022. doi: 10.1145/3508352.3561098.