Biblio
With the growing scale of Cyber-Physical Systems (CPSs), it is challenging to maintain their stability under all operating conditions. How to reduce the downtime and locate the failures becomes a core issue in system design. In this paper, we employ a hierarchical contract-based resilience framework to guarantee the stability of CPS. In this framework, we use Assume Guarantee (A-G) contracts to monitor the non-functional properties of individual components (e.g., power and latency), and hierarchically compose such contracts to deduce information about faults at the system level. The hierarchical contracts enable rapid fault detection in large-scale CPS. However, due to the vast number of components in CPS, manually designing numerous contracts and the hierarchy becomes challenging. To address this issue, we propose a technique to automatically decompose a root contract into multiple lower-level contracts depending on I/O dependencies between components. We then formulate a multi-objective optimization problem to search the optimal parameters of each lower-level contract. This enables automatic contract refinement taking into consideration the communication overhead between components. Finally, we use a case study from the manufacturing domain to experimentally demonstrate the benefits of the proposed framework.
To meet the growing railway-transportation demand, a new train control system, communication-based train control (CBTC) system, aims to maximize the ability of train lines by reducing the headway of each train. However, the wireless communications expose the CBTC system to new security threats. Due to the cyber-physical nature of the CBTC system, a jamming attack can damage the physical part of the train system by disrupting the communications. To address this issue, we develop a secure framework to mitigate the impact of the jamming attack based on a security criterion. At the cyber layer, we apply a multi-channel model to enhance the reliability of the communications and develop a zero-sum stochastic game to capture the interactions between the transmitter and jammer. We present analytical results and apply dynamic programming to find the equilibrium of the stochastic game. Finally, the experimental results are provided to evaluate the performance of the proposed secure mechanism.