RODD: An effective reference-based outlier detection technique for large datasets

Abstract

Outlier detection has gained considerable interest in several fields of research including various sciences, medical diagnosis, fraud detection, and network intrusion detection. Most existing techniques are either distance based or density based. In this paper, we present an effective reference point based outlier detection technique (RODD) which performs satisfactorily in high dimensional real-world datasets. The technique was evaluated in terms of detection rate and false positive rate over several synthetic and real-world datasets and the performance is excellent. © Springer-Verlag Berlin Heidelberg 2011.