DocumentCode
1781070
Title
An on-line anomaly detection method based on LMS algorithm
Author
Ziyu Wang ; Jiahai Yang ; Fuliang Li
Author_Institution
Tsinghua Nat. Lab. for Inf. Sci. & Technol. (TNList), Tsinghua Univ., Beijing, China
fYear
2014
fDate
17-19 Sept. 2014
Firstpage
1
Lastpage
6
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.
Keywords
fault diagnosis; least mean squares methods; telecommunication security; IGFE; IGTE; LMS algorithm; LMS-based detector; linear correlation; online anomaly detection method; zero attacks detection; Correlation; Detectors; Equations; IP networks; Least squares approximations; Mathematical model; Vectors; IGFE; IGTE; Least Mean Square; anomaly detection;
fLanguage
English
Publisher
ieee
Conference_Titel
Network Operations and Management Symposium (APNOMS), 2014 16th Asia-Pacific
Conference_Location
Hsinchu
Type
conf
DOI
10.1109/APNOMS.2014.6996537
Filename
6996537
Link To Document