1. A method comprising: constructing a first collection, the first collection comprising a first feature vector and a Q&A feature vector; constructing a second collection from the first collection by inserting noise data in at least one of the first feature vector and the Q&A feature vector; further constructing a third collection by combining, to crossover, a feature vector of the second collection with a corresponding feature vector of a fourth collection, wherein the second and the fourth collections have a property similar to one another; aging, using a forecasting configuration, a first feature vector of the third collection to generate a changed feature vector, the changed feature vector containing feature values expected at a future time; predicting, by inputting the changed feature vector in a trained neural network, a probability of the cyber-attack occurring at the future time.