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» Data Mining for Intrusion Detection: From Outliers to True I...
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KDD
2002
ACM
144views Data Mining» more  KDD 2002»
14 years 5 months ago
ADMIT: anomaly-based data mining for intrusions
Security of computer systems is essential to their acceptance and utility. Computer security analysts use intrusion detection systems to assist them in maintaining computer system...
Karlton Sequeira, Mohammed Javeed Zaki
KDD
2006
ACM
156views Data Mining» more  KDD 2006»
14 years 5 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 ...
DATAMINE
2006
164views more  DATAMINE 2006»
13 years 5 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...
ICDM
2003
IEEE
170views Data Mining» more  ICDM 2003»
13 years 10 months ago
Algorithms for Spatial Outlier Detection
A spatial outlier is a spatially referenced object whose non-spatial attribute values are significantly different from the values of its neighborhood. Identification of spatial ...
Chang-Tien Lu, Dechang Chen, Yufeng Kou
APNOMS
2008
Springer
13 years 7 months ago
Application of Data Mining to Network Intrusion Detection: Classifier Selection Model
As network attacks have increased in number and severity over the past few years, intrusion detection system (IDS) is increasingly becoming a critical component to secure the netwo...
Huy Anh Nguyen, Deokjai Choi