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151
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KDD
2008
ACM
195views Data Mining» more  KDD 2008»
16 years 2 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
120
Voted
IMC
2010
ACM
15 years 11 days 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
15 years 7 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...
124
Voted
AIPR
2008
IEEE
15 years 9 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
127
Voted
AI
2006
Springer
15 years 6 months 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