An on-line anomaly detection method based on LMS algorithm

Abstract

Anomaly detection has been a hot topic in recent years due to its capability of detecting zero attacks. In this paper, we propose a new on-line anomaly detection method based on LMS algorithm. The basic idea of the LMS-based detector is to predict IGTE using IGFE, given the high linear correlation between them. Using the artificial synthetic data, it is shown that the LMS-based detector possesses strong detection capability, and its false positive rate is within acceptable scope.