Detecting human vulnerably in socio-technical systems: a naval case study.

The increasing number of cyberattacks requires to incorporate security concerns all along the system development life-cycle. In this context, detecting and evaluating vulnerabilities early in system modelling helps fix security issues and improves resilience of systems. Nowadays, due to the increasing complexity of modern systems, the level of responsibility dedicated to human operator has growning up. This is particularly visible in Socio-Technical Systems (STS) where humans are considered as subsystems. Thus, to improve the resilience of the overall system, it is necessary to manage the vulnerability of humans. We developed a language called HoS-ML and a specific tool allowing a system architect to evaluate human vulnerability in STS during early stage of the system design. In this paper we present an industrial STS case study using our approach. We briefly present the language and his metamodel before to model a real industrial case study to illustrate our approach..