The deployment and use of Anomaly Detection (AD) sensors often requires the intervention of a human expert to manually calibrate and optimize their performance. Depending on the si...
Gabriela F. Cretu-Ciocarlie, Angelos Stavrou, Mich...
This paper presents a novel host-based combinatorial method based on k-Means clustering and ID3 decision tree learning algorithms for unsupervised classification of anomalous and ...
Artificial immune systems, more specifically the negative selection algorithm, have previously been applied to intrusion detection. The aim of this research is to develop an intrus...
—Anomaly detection is an important challenge for tasks such as fault diagnosis and intrusion detection in energy constrained wireless sensor networks. A key problem is how to min...
Sutharshan Rajasegarar, Christopher Leckie, Marimu...
This paper addresses the task of change analysis of correlated multi-sensor systems. The goal of change analysis is to compute the anomaly score of each sensor when we know that t...