In this paper we discuss a data mining framework for constructing intrusion detection models. The key ideas are to mine system audit data for consistent and useful patterns of pro...
Detecting and diagnosing errors in novice behavior is an important student modeling task. In this paper, we describe MEDD, an unsupervised incremental multistrategy system for the ...
We present Cluster Onset Detection (COD), a novel algorithm to aid in detection of epidemic outbreaks. COD employs unsupervised learning techniques in an online setting to partiti...
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. It is commonly accepted that intrusion detection systems (IDS) are required to compensate for the insufficient security mechanisms that are available on computer systems...