Probabilistic High-Level Estimation of Vulnerability and Fault Mitigation of Critical Systems Using Fault-Mitigation Trees (FMTs)

摘要

The development of safety-critical systems is a rather challenging task, especially due to the cost and complexity associated with this endeavor. For this reason, early fault assessment is a key element towards minimizing vulnerability at the design stage of development. Existing early analysis techniques are often unable to conduct a comprehensive and exhaustive analysis on complex redundant architectures, which may lead to less than optimal risk evaluation. This paper seeks to address some of these issues by proposing a high-level analysis methodology based on probabilistic model checking. This analysis is done by introducing new probabilistic models for repairable fault trees described in the Continuous-Time Markov Decision Process formalism. The models include repairable components and redundancy partitioning to evaluate fault vulnerability across different implementations of the system. The presented approach is very scalable and results demonstrate that the proposed analysis is as reliable as physical FPGA testing, in some scenarios.