The ubiquity of the Internet connection to desktops has been both boon to business as well as cause for concern for the security of digital assets that may be unknowingly exposed....
This research employs unsupervised pattern recognition to approach the thorny issue of detecting anomalous network behavior. It applies a connectionist model to identify user behav...
In this paper we propose a peer-to-peer (P2P) prototype (INTCTD) for intrusion detection over an overlay network. INTCTD is a distributed system based on neural networks for detec...
Abstract— A clear deficiency in most of todays Anomaly Intrusion Detection Systems (AIDS) is their inability to distinguish between a new form of legitimate normal behavior and ...
This paper investigates the suitability of linear genetic programming (LGP) technique to model efficient intrusion detection systems, while comparing its performance with artificia...