Risk-based failure modeling is a process used to understand the impact, likelihood and ability of detecting the various ways that a system can fail. Delivery teams are starting to use this methodology to design and evaluate the controls needed to prevent these failures. The approach is based on the practice of (FMEA), a risk-scoring technique that has been around since the 1940s and with a successful track record in industries that build complex physical systems such as aerospace and automotive. As with those industries, software failure can also have dire consequences — compromising, for example, human health and privacy — which is why we're seeing an increased need for systems to undergo rigorous analysis. The process starts by identifying the possible failure modes. The team then performs a root cause analysis and assigns scores according to the likelihood of a failure occurring, the size of its impact and the probability of detecting the root cause of the failure. We've found this to be most effective when cross-functional teams iterate through this process as the system evolves. When it comes to security, risk-based failure modeling can be a useful complement to threat modeling and attack path analysis.
