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» On Detecting Clustered Anomalies Using SCiForest
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ICPPW
2008
IEEE
15 years 3 months ago
Disparity: Scalable Anomaly Detection for Clusters
In this paper, we describe disparity, a tool that does parallel, scalable anomaly detection for clusters. Disparity uses basic statistical methods and scalable reduction operation...
Narayan Desai, Rick Bradshaw, Ewing L. Lusk
INFOCOM
2010
IEEE
14 years 8 months ago
URCA: Pulling out Anomalies by their Root Causes
—Traffic anomaly detection has received a lot of attention over recent years, but understanding the nature of these anomalies and identifying the flows involved is still a manu...
Fernando Silveira, Christophe Diot
TJS
2010
182views more  TJS 2010»
14 years 7 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
ICIP
2007
IEEE
15 years 11 months ago
Unsupervised Modeling of Object Tracks for Fast Anomaly Detection
A key goal of far-field activity analysis is to learn the usual pattern of activity in a scene and to detect statistically anomalous behavior. We propose a method for unsupervised...
Tomas Izo, W. Eric L. Grimson
VLDB
2007
ACM
164views Database» more  VLDB 2007»
15 years 9 months ago
A new intrusion detection system using support vector machines and hierarchical clustering
Whenever an intrusion occurs, the security and value of a computer system is compromised. Network-based attacks make it difficult for legitimate users to access various network ser...
Latifur Khan, Mamoun Awad, Bhavani M. Thuraisingha...