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» Detecting Anomalies and Intruders
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KDD
2008
ACM
195views Data Mining» more  KDD 2008»
14 years 10 months ago
Anomaly pattern detection in categorical datasets
We propose a new method for detecting patterns of anomalies in categorical datasets. We assume that anomalies are generated by some underlying process which affects only a particu...
Kaustav Das, Jeff G. Schneider, Daniel B. Neill
ICIP
2009
IEEE
14 years 10 months ago
Detecting Contextual Anomalies Of Crowd Motion In Surveillance Video
Many works have been proposed on detecting individual anomalies in crowd scenes, i.e., human behaviors anomalous with respect to the rest of the behaviors. In this paper, we intro...
SECURWARE
2008
IEEE
14 years 4 months ago
ToLeRating UR-STD
A new emerging paradigm of Uncertain Risk of Suspicion, Threat and Danger, observed across the field of information security, is described. Based on this paradigm a novel approac...
Jan Feyereisl, Uwe Aickelin
ACSC
2005
IEEE
14 years 3 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
CSDA
2010
124views more  CSDA 2010»
13 years 9 months ago
Statistical inference on attributed random graphs: Fusion of graph features and content
Abstract: Fusion of information from graph features and content can provide superior inference for an anomaly detection task, compared to the corresponding content-only or graph fe...
John Grothendieck, Carey E. Priebe, Allen L. Gorin