Classification of computer intrusions using functional networks. A comparative study

Intrusion detection is a problem that has attracted a great deal of attention from computer scientists recently, due to the exponential increase in computer attacks in recent years. DARPA KDD Cup 99 is a standard dataset for classifying computer attacks, to which several machine learning techniques have been applied. In this paper, we describe the results obtained using functional networks – a paradigm that extends feedforward neural networks – and compare these to the results obtained for other techniques applied to the same dataset. Of particular interest is the capacity for generalization of the approach used.