1. A method for predicting a sequence of cyber events comprising: collecting baseline cyber event patterns and storing the baseline cyber event patterns in a cyber event repository; searching the baseline cyber event patterns for sequential patterns and storing the sequential patterns in a pattern repository; translating the sequential patterns into a probabilistic graphical model; wherein the probabilistic graphical model is a Dynamic Bayesian Network prediction model; and using a temporal reasoning engine to feed the probabilistic graphical model with current cyber event sequences and predict future cyber events and the probability the future events will happen in a next time window.
1. A method for predicting a sequence of cyber events comprising: collecting baseline cyber event patterns and storing the baseline cyber event patterns in a cyber event repository; searching the baseline cyber event patterns for sequential patterns and storing the sequential patterns in a pattern repository; translating the sequential patterns into a probabilistic graphical model; wherein the probabilistic graphical model is a Dynamic Bayesian Network prediction model; and using a temporal reasoning engine to feed the probabilistic graphical model with current cyber event sequences and predict future cyber events and the probability the future events will happen in a next time window. 2. The method of claim 1 , wherein the baseline cyber events are collected by executing sequential cyber event mining algorithms.