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» Detecting Anomalies and Intruders
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DATAMINE
2006
164views more  DATAMINE 2006»
13 years 7 months ago
Fast Distributed Outlier Detection in Mixed-Attribute Data Sets
Efficiently detecting outliers or anomalies is an important problem in many areas of science, medicine and information technology. Applications range from data cleaning to clinica...
Matthew Eric Otey, Amol Ghoting, Srinivasan Partha...
AINA
2004
IEEE
13 years 11 months ago
Online Training of SVMs for Real-time Intrusion Detection
Abstract-- As intrusion detection essentially can be formulated as a binary classification problem, it thus can be solved by an effective classification technique-Support Vector Ma...
Zonghua Zhang, Hong Shen
TIFS
2008
154views more  TIFS 2008»
13 years 7 months ago
Data Fusion and Cost Minimization for Intrusion Detection
Abstract--Statistical pattern recognition techniques have recently been shown to provide a finer balance between misdetections and false alarms than the more conventional intrusion...
Devi Parikh, Tsuhan Chen
CN
2000
95views more  CN 2000»
13 years 7 months ago
The 1999 DARPA off-line intrusion detection evaluation
Abstract. Eight sites participated in the second DARPA off-line intrusion detection evaluation in 1999. A test bed generated live background traffic similar to that on a government...
Richard Lippmann, Joshua W. Haines, David J. Fried...
KDD
2006
ACM
156views Data Mining» more  KDD 2006»
14 years 7 months ago
Detecting outliers using transduction and statistical testing
Outlier detection can uncover malicious behavior in fields like intrusion detection and fraud analysis. Although there has been a significant amount of work in outlier detection, ...
Daniel Barbará, Carlotta Domeniconi, James ...