Software systems intelligence has been increased to deliver a greater wealth of functionalities in numerous domains, such as defence and smart cities.
These solutions are application domains of a specific type of systems called System-of-Systems (SoS).
The challenge that we address is: how can we anticipate cyberattacks early at the architecture phase of the SoS development lifecycle to avoid time and cost wastage and to prevent massive damages impacting people’s safety and security?
Our task was to analyse the log file from the execution/simulation of the secure SoS architecture, automatically generate a visual diagram representing the potential cascading attacks targeting this architecture, and provide meaningful feedback to architects about the possible security solutions and correctness actions to be taken. The project uses Model Driven Engineering and text mining techniques. It explores security databases to identify attack patterns and propose security patterns to mitigate the discovered vulnerabilities.
Mai Anh Khoa Nguyen