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» Mining Several Data Bases with an Ensemble of Classifiers
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CIA
2008
Springer
13 years 9 months ago
Trust-Based Classifier Combination for Network Anomaly Detection
Abstract. We present a method that improves the results of network intrusion detection by integration of several anomaly detection algorithms through trust and reputation models. O...
Martin Rehák, Michal Pechoucek, Martin Gril...
SDM
2007
SIAM
96views Data Mining» more  SDM 2007»
13 years 9 months ago
Understanding and Utilizing the Hierarchy of Abnormal BGP Events
Abnormal events, such as security attacks, misconfigurations, or electricity failures, could have severe consequences toward the normal operation of the Border Gateway Protocol (...
Dejing Dou, Jun Li, Han Qin, Shiwoong Kim, Sheng Z...
SDM
2004
SIAM
174views Data Mining» more  SDM 2004»
13 years 9 months ago
Classifying Documents Without Labels
Automatic classification of documents is an important area of research with many applications in the fields of document searching, forensics and others. Methods to perform classif...
Daniel Barbará, Carlotta Domeniconi, Ning K...
ICDM
2007
IEEE
199views Data Mining» more  ICDM 2007»
14 years 2 months ago
Discovering Structural Anomalies in Graph-Based Data
The ability to mine data represented as a graph has become important in several domains for detecting various structural patterns. One important area of data mining is anomaly det...
William Eberle, Lawrence B. Holder
PAKDD
2000
ACM
161views Data Mining» more  PAKDD 2000»
13 years 11 months ago
Adaptive Boosting for Spatial Functions with Unstable Driving Attributes
Combining multiple global models (e.g. back-propagation based neural networks) is an effective technique for improving classification accuracy by reducing a variance through manipu...
Aleksandar Lazarevic, Tim Fiez, Zoran Obradovic