6. A computer program product embodied on a non-transitory computer readable medium and configured to execute by a microprocessor, the computer program product comprising a method for predicting a sequence of cyber events by computer instructions 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 events and predict future cyber events and the probability the future cyber events will happen in a next time window.
6. A computer program product embodied on a non-transitory computer readable medium and configured to execute by a microprocessor, the computer program product comprising a method for predicting a sequence of cyber events by computer instructions 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 events and predict future cyber events and the probability the future cyber events will happen in a next time window. 7. The computer program product of claim 6 , wherein the baseline cyber events are collected by executing sequential event mining algorithms.