Security-Aware Modeling and Efficient Mapping for CAN-Based Real-Time Distributed Automotive Systems

Security has become a critical issue for automotive electronic systems. To protect against attacks, security mechanisms have to be applied, but the overhead of those mechanisms may impede system performance and cause violations of design constraints. To remedy this problem, we proposed an integrated mixed integer linear programming (MILP) formulation that is the first to address both security and safety constraints during system mapping for controller area network (CAN) based systems. However, its signal-based security constraints do not fully reflect real security requirements, and its objective function is to minimize functional path latencies rather than minimize security risk. Furthermore, its MILP-based approach has high computation complexity. In this work, we present a new formulation that defines path-based security constraints and minimizes security risk directly, and propose a new heuristic algorithm to solve the formulation efficiently. Experiments on an industrial example show that our new algorithm achieves comparable solution quality as the MILP-based approach with much better efficiency.