Abstract. We propose a novel framework of autonomic intrusion detection that fulfills online and adaptive intrusion detection in unlabeled audit data streams. The framework owns a...
An established method to detect concept drift in data streams is to perform statistical hypothesis testing on the multivariate data in the stream. Statistical decision theory off...
Abstract. Data stream mining has become a novel research topic of growing interest in knowledge discovery. Most proposed algorithms for data stream mining assume that each data blo...
Detection of web attacks is an important issue in current defense-in-depth security framework. In this paper, we propose a novel general framework for adaptive and online detectio...
Wei Wang 0012, Florent Masseglia, Thomas Guyet, Re...
The primary constraint in the effective mining of data streams is the large volume of data which must be processed in real time. In many cases, it is desirable to store a summary...