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PAKDD
2009
ACM
115views Data Mining» more  PAKDD 2009»
13 years 10 months ago
Data Mining for Intrusion Detection: From Outliers to True Intrusions
Data mining for intrusion detection can be divided into several sub-topics, among which unsupervised clustering has controversial properties. Unsupervised clustering for intrusion...
Goverdhan Singh, Florent Masseglia, Céline ...
ICMLA
2004
13 years 5 months ago
Outlier detection and evaluation by network flow
Detecting outliers is an important topic in data mining. Sometimes the outliers are more interesting than the rest of the data. Outlier identification has lots of applications, su...
Ying Liu, Alan P. Sprague
ICDM
2005
IEEE
187views Data Mining» more  ICDM 2005»
13 years 9 months ago
Parallel Algorithms for Distance-Based and Density-Based Outliers
An outlier is an observation that deviates so much from other observations as to arouse suspicion that it was generated by a different mechanism. Outlier detection has many applic...
Elio Lozano, Edgar Acuña
CSREASAM
2006
13 years 5 months ago
Novel Attack Detection Using Fuzzy Logic and Data Mining
: - Intrusion Detection Systems are increasingly a key part of systems defense. Various approaches to Intrusion Detection are currently being used, but they are relatively ineffect...
Norbik Bashah Idris, Bharanidharan Shanmugam
IDEAS
2008
IEEE
256views Database» more  IDEAS 2008»
13 years 10 months ago
WIDS: a sensor-based online mining wireless intrusion detection system
This paper proposes WIDS, a wireless intrusion detection system, which applies data mining clustering technique to wireless network data captured through hardware sensors for purp...
Christie I. Ezeife, Maxwell Ejelike, Akshai K. Agg...