Survival Analysis for attacks anomaly detection

Description: Survival analysis is a statistical technique used to analyze data and often used to study the time until an event occurs, such as the time until a machine fails or the time until a customer cancels a subscription. In the context of IoT systems, survival analysis models such as Cox proportional hazards models or accelerated failure time models in order to estimate that time and detect anomalies or a security breach which may not be apparent with other statistical methods. For example, this models could estimate the survival function based on the patterns normal data have and compare it with the one estimated when there is a possible anomaly or some attacks like fuzzy, malfunction and flooding.