With the increasing deployment in mission-critical domains, it is of foremost importance to improve dependability of distributed real-time applications for cyber–physical systems (CPSs) with safety & security-critical threats. Different from existing works addressing the security or safety design separately, this article makes efforts to achieve the safety and security co-design from system-level perspective, especially considering the interplay between fault tolerance and security harden techniques. To guarantee the safety of real-time applications, fault-tolerant techniques, e.g., task re-execution and active replica, are leveraged to tolerate faults in task executions. To improve the security of distributed applications, cryptography is deployed to resist confidentiality attacks on messages delivered over the communication media. We analyze the impact of task’s fault tolerance on secure message communication, and then formulate the design problem as a multiobjective optimization problem, i.e., to minimize the failure probability and security vulnerability of the application while subject to given fault-tolerant constraints, execution constraints and deadline constraints. Since the optimization problem is NP-hard, we then propose an improved multiobjective optimization algorithm, called decomposition-based dependability co-optimization (DeDeCo) algorithm, to search for the optimal Pareto solutions of security and reliability harden assignments for messages and tasks, respectively. Extensive experiments and an industrial case evaluate the efficiency of DeDeCo, indicating that our design and optimization algorithm are suitable for improving the dependability of real-time applications running on security & safety-critical CPSs.

Confidentiality-Specific Faults (CSFs) will put cyber physical systems in threat, since they can result in corrupted information or even retrieve the cryptographic key of security-critical applications. In this paper, we will look into fault-tolerant co-design optimization for security-critical cyber physical systems with resource constraints, such that the encryption/decryption of confidential messages are protected against transient CSF faults. We consider imperfect fault detection mechanisms to identify transient CSF faults happened on confidentiality protection, and utilize duplication code to recovery from such faults. We utilize FPGA to accelerate the executions of security tasks, reducing the overheads of fault-tolerant implementations. The system-level design problem is formulated as a two-objective optimization problem, i.e., to minimize the average reliability degradation of the fault tolerant assignments and to minimize the balanced degree of the reliability degradation, subject to available FPGA budget, deadline, and application execution constraints. Since finding Pareto-optimal solutions is NP-hard, we propose an improved multi-objective optimization algorithm, called DEcomposition-based Security Co-design Optimization (DESCO), to search for Pareto-optimal solutions of fault-tolerant assignments. Experimental results demonstrate that DESCO is effective and can outperform other candidates, proving that our approach is promising in dealing with system-level optimization problem for security-critical applications on cyber physical systems.

In this paper, we focus on improving the resilience of distributed real-time applications for Cyber Physical Systems. To guarantee the safety related resilience, fault-tolerant techniques, e.g., task re-execution and active replica, are leveraged to tolerate faults in task executions. To provide security related resilience, cryptography is deployed to resist confidentiality attack on messages delivered over the communication media. We analyze the impact of task’s fault tolerance on secure message communication, and then formulate the design problem as a multi-objective optimization problem, i.e., to minimize the failure probability and security vulnerability of the application while subject to given fault-tolerant constraints, execution constraints and deadline constraints. We propose an improved multi-objective optimization algorithm, called Decomposition-based Security and Fault tolerance Co-Optimization (DeSFCO) algorithm, to search for the optimal Pareto solutions of security and reliability harden assignments for messages and tasks. Two preliminary experiments evaluate efficiency of our approach.