Dr Martin Barrere Cambrun
Academic and research departments
Surrey Centre for Cyber Security, Department of Computer Science, Faculty of Engineering and Physical Sciences.About
Biography
Dr Martin Barrere is a Lecturer in Digital Resilience at the Department of Computer Science, University of Surrey, UK, and an Honorary Research Fellow at the Institute for Security Science and Technology at Imperial College London, UK. His current research work focuses on Cyber Security for Critical National Infrastructure.
Before joining Surrey in April 2023, he was a postdoctoral Cyber Security Researcher at the Department of Computing (2014-2018) and later on at the Institute for Security Science and Technology (2018-2023) at Imperial College London, UK. In 2020, he was awarded a GCHQ Research Fellowship for National Resilience.
Dr Barrere received his PhD degree in Computer Science from the University of Lorraine / INRIA, France, in 2014. Prior to this, he worked in both academic and industry domains during several years, undertaking professional roles as CTO, network and system administrator, and software developer, in different companies. Dr Barrere is a frequent reviewer for several conferences and journals, serves in the technical program committees of various international conferences, and is an Associate Editor for the Journal of Network and Systems Management.
Dr Barrere's research publications can be found at Google Scholar or DBLP, among others.
Areas of specialism
ResearchResearch interests
His main research interests include network security, cyber-physical systems, attack graphs, security metrics, network management, risk analysis, autonomic computing, probabilistic graphical models, and forensic investigations.
Research interests
His main research interests include network security, cyber-physical systems, attack graphs, security metrics, network management, risk analysis, autonomic computing, probabilistic graphical models, and forensic investigations.
Publications
Cyber-Physical Systems (CPS) often involve complex networks of interconnected software and hardware components that are logically combined to achieve a common goal or mission; for example, keeping a plane in the air or providing energy to a city. Failures in these components may jeopardise the mission of the system. Therefore, identifying the minimal set of critical CPS components that is most likely to fail, and prevent the global system from accomplishing its mission, becomes essential to ensure reliability. In this article, we present a novel approach to identifying the Most Likely Mission-critical Component Set (MLMCS) using AND/OR dependency graphs enriched with independent failure probabilities. We address the MLMCS problem as a Maximum Satisfiability (MaxSAT) problem. We translate probabilities into a negative logarithmic space to linearise the problem within MaxSAT. The experimental results conducted with our open source tool LDA4CPS indicate that the approach is both effective and efficient. We also present a case study on complex aircraft systems that shows the feasibility of our approach and its applicability to mission-critical cyber-physical systems. Finally, we present two MLMCS-based security applications focused on system hardening and forensic investigations.