Security-critical distributed systems have faced with malicious snooping and fault injection attack challenges. Traditional researches mainly focus on preventing malicious snooping which disregard fault injection attack threat. Concerning the above problem, the fault detection for message' encryption/decryption was considered, to maximize the fault coverage and minimize the heterogeneous degree of the messages' fault coverage. Firstly, Advanced Encryption Standard (AES) was used to protect confidentiality. Secondly, five fault detection schemes were proposed, and their fault coverage rates and time overheads were derived and measured, respectively. Finally, an efficient heuristic algorithm based on Simulated Annealing (SA) under the real-time constraint was proposed, which can maximize the fault coverage and minimize the heterogeneity. The experimental results show that the objective function value achieved by the proposed algorithm is 18% higher than that of the greedy algorithm at least, verifying the efficiency and robustness of the proposed algorithm.

The WCET (Worst Case Execution Time) is taken as the actual execution time of the task, which may cause a great waste of system resource. In order to solve the problem, a method based on stochastic task probability model was proposed. Firstly, Dynamic Voltage and Frequency Scaling (DVFS) was utilized to reduce the energy consumption by considering the effect of DVFS on the reliability of the system, the specific probability distribution of task execution time and the task requirement of No-Deadline Violation Probability (NDVP). Then, a new optimization algorithm with the operation time of polynomial was proposed based on the dynamic programming algorithm. In addition, the execution overhead of the algorithm was reduced by designing the state eliminating rules. The simulation results show that, compared with the optimal algorithm of the model of WCET, the proposed algorithm can reduce the system energy consumption by more than 30%. The experimental results indicate that considering the random execution time of tasks can save the system resources while ensuring the reliability of the system.