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PVLDB
2010
117views more  PVLDB 2010»
14 years 8 months ago
Distance-Based Outlier Detection: Consolidation and Renewed Bearing
Detecting outliers in data is an important problem with interesting applications in a myriad of domains ranging from data cleaning to financial fraud detection and from network i...
Gustavo Henrique Orair, Carlos Teixeira, Ye Wang, ...
KDD
2006
ACM
156views Data Mining» more  KDD 2006»
15 years 10 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 ...
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DATAMINE
2006
164views more  DATAMINE 2006»
14 years 10 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...
KDD
2002
ACM
157views Data Mining» more  KDD 2002»
15 years 10 months ago
Learning nonstationary models of normal network traffic for detecting novel attacks
Traditional intrusion detection systems (IDS) detect attacks by comparing current behavior to signatures of known attacks. One main drawback is the inability of detecting new atta...
Matthew V. Mahoney, Philip K. Chan
CCS
2006
ACM
15 years 1 months ago
Evading network anomaly detection systems: formal reasoning and practical techniques
Attackers often try to evade an intrusion detection system (IDS) when launching their attacks. There have been several published studies in evasion attacks, some with available to...
Prahlad Fogla, Wenke Lee