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ADBIS
2006
Springer
200views Database» more  ADBIS 2006»
13 years 11 months ago
Anomaly Detection Using Unsupervised Profiling Method in Time Series Data
The anomaly detection problem has important applications in the field of fraud detection, network robustness analysis and intrusion detection. This paper is concerned with the prob...
Zakia Ferdousi, Akira Maeda
SDM
2009
SIAM
291views Data Mining» more  SDM 2009»
14 years 2 months ago
Detection and Characterization of Anomalies in Multivariate Time Series.
Anomaly detection in multivariate time series is an important data mining task with applications to ecosystem modeling, network traffic monitoring, medical diagnosis, and other d...
Christopher Potter, Haibin Cheng, Pang-Ning Tan, S...
ADMA
2006
Springer
112views Data Mining» more  ADMA 2006»
13 years 11 months ago
Finding Time Series Discords Based on Haar Transform
The problem of finding anomaly has received much attention recently. However, most of the anomaly detection algorithms depend on an explicit definition of anomaly, which may be i...
Ada Wai-Chee Fu, Oscar Tat-Wing Leung, Eamonn J. K...
NOMS
2010
IEEE
251views Communications» more  NOMS 2010»
13 years 3 months ago
Online detection of utility cloud anomalies using metric distributions
—The online detection of anomalies is a vital element of operations in data centers and in utility clouds like Amazon EC2. Given ever-increasing data center sizes coupled with th...
Chengwei Wang, Vanish Talwar, Karsten Schwan, Part...
ACSC
2005
IEEE
13 years 10 months ago
Unsupervised Anomaly Detection in Network Intrusion Detection Using Clusters
Most current network intrusion detection systems employ signature-based methods or data mining-based methods which rely on labelled training data. This training data is typically ...
Kingsly Leung, Christopher Leckie