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CNSR
2008
IEEE
108views Communications» more  CNSR 2008»
13 years 10 months ago
A Novel Covariance Matrix Based Approach for Detecting Network Anomalies
During the last decade, anomaly detection has attracted the attention of many researchers to overcome the weakness of signature-based IDSs in detecting novel attacks. However, hav...
Mahbod Tavallaee, Wei Lu, Shah Arif Iqbal, Ali A. ...
RAID
2004
Springer
13 years 9 months ago
Anomaly Detection Using Layered Networks Based on Eigen Co-occurrence Matrix
Anomaly detection is a promising approach to detecting intruders masquerading as valid users (called masqueraders). It creates a user profile and labels any behavior that deviates...
Mizuki Oka, Yoshihiro Oyama, Hirotake Abe, Kazuhik...
SDM
2009
SIAM
202views Data Mining» more  SDM 2009»
14 years 1 months ago
Proximity-Based Anomaly Detection Using Sparse Structure Learning.
We consider the task of performing anomaly detection in highly noisy multivariate data. In many applications involving real-valued time-series data, such as physical sensor data a...
Tsuyoshi Idé, Aurelie C. Lozano, Naoki Abe,...
ICANNGA
2009
Springer
201views Algorithms» more  ICANNGA 2009»
13 years 11 months ago
A Novel Signal-Based Approach to Anomaly Detection in IDS Systems
In this paper we present our original methodology, in which Matching Pursuit is used for networks anomaly and intrusion detection. The architecture of anomaly-based IDS based on si...
Lukasz Saganowski, Michal Choras, Rafal Renk, Wito...
TJS
2010
182views more  TJS 2010»
13 years 2 months ago
A novel unsupervised classification approach for network anomaly detection by k-Means clustering and ID3 decision tree learning
This paper presents a novel host-based combinatorial method based on k-Means clustering and ID3 decision tree learning algorithms for unsupervised classification of anomalous and ...
Yasser Yasami, Saadat Pour Mozaffari