A novel boosting-based anomaly detection scheme

As a crucial issue in computer network security, anomaly detection is receiving more and more attention from both application and theoretical point of view. In this paper, by introducing boosting technique, a novel anomaly detection scheme is proposed. On the whole, the proposed scheme is based on Ada-Boost and can be viewed as an extension of Ada-Boost in terms of both probability density estimation (PDE) and confidence area estimation (CAE). Different kinds of base learners are adopted and investigated in the proposed scheme. Systematic experimental results on DARPA 1999 dataset validate the effectiveness of the proposed scheme.