Biblio

The introduction of automation in cyber-physical systems (CPS) has raised major safety and security concerns. One attack vector is the sensing unit whose measurements can be manipulated by an adversary through attacks such as denial of service and delay injection. To secure an autonomous CPS from such attacks, we use a challenge response authentication (CRA) technique for detection of attack in active sensors data and estimate safe measurements using the recursive least square algorithm. For demonstrating effectiveness of our proposed approach, a car-follower model is considered where the follower vehicle's radar sensor measurements are manipulated in an attempt to cause a collision.

Untrusted third-party vendors and manufacturers have raised security concerns in hardware supply chain. Among all existing solutions, formal verification methods provide powerful solutions in detection malicious behaviors at the pre-silicon stage. However, little work have been done towards built-in hardware runtime verification at the post-silicon stage. In this paper, a runtime formal verification framework is proposed to evaluate the trust of hardware during its execution. This framework combines the symbolic execution and SAT solving methods to validate the user defined properties. The proposed framework has been demonstrated on an FPGA platform using an SoC design with untrusted IPs. The experimentation results show that the proposed approach can provide high-level security assurance for hardware at runtime.