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KDD
2008
ACM
195views Data Mining» more  KDD 2008»
14 years 8 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
IMC
2010
ACM
13 years 6 months ago
Temporally oblivious anomaly detection on large networks using functional peers
Previous methods of network anomaly detection have focused on defining a temporal model of what is "normal," and flagging the "abnormal" activity that does not...
Kevin M. Carter, Richard Lippmann, Stephen W. Boye...
RAID
2004
Springer
14 years 1 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...
AIPR
2008
IEEE
14 years 2 months ago
Temporal structure methods for image-based change analysis
– This paper addresses the exploitation of massive numbers of image-derived change detections. We use the term “change analysis” to emphasize the intelligence value obtained ...
Ray Rimey, Dan Keefe
AI
2006
Springer
14 years 5 days ago
Adaptive Fraud Detection Using Benford's Law
Abstract. Adaptive Benford's Law [1] is a digital analysis technique that specifies the probabilistic distribution of digits for many commonly occurring phenomena, even for in...
Fletcher Lu, J. Efrim Boritz, H. Dominic Covvey