DESCO: Decomposition-Based Co-Design to Improve Fault Tolerance of Security-Critical Tasks in Cyber Physical Systems

• Published in: IEEE transactions on computers Vol. 72; no. 6; pp. 1 - 14
• Main Authors: Jiang, Wei, Liao, Xinke, Zhan, Jinyu, Adhikari, Deepak, Jiang, Ke
• Format: Journal Article
• Language: English
• Published: New York IEEE 01.06.2023; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Algorithms; Co-design; Confidentiality; Confidentiality-Specific Faults; Cryptography; Cyber-physical systems; Decomposition; Decomposition-based Optimization; Degradation; Design optimization; Encryption; Fault detection; Fault tolerance; Fault tolerant systems; Faults; Field programmable gate arrays; Information retrieval; Multiple objective analysis; Pareto optimization; Pareto optimum; Reliability; Security; Security Co-Design; Security-Critical Cyber Physical Systems; Task analysis; Transient analysis
• DOI: 10.1109/TC.2022.3218987
• ISSN: 0018-9340

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.