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» Combined Data Mining Approach for Intrusion Detection
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PAKDD
2009
ACM
115views Data Mining» more  PAKDD 2009»
14 years 3 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 ...
IRI
2005
IEEE
14 years 2 months ago
Exploiting efficient data mining techniques to enhance intrusion detection systems
- Security is becoming a critical part of organizational information systems. Intrusion Detection System (IDS) is an important detection that is used as a countermeasure to preserv...
Chang-Tien Lu, Arnold P. Boedihardjo, Prajwal Mana...
GPEM
2010
134views more  GPEM 2010»
13 years 7 months ago
An ensemble-based evolutionary framework for coping with distributed intrusion detection
A distributed data mining algorithm to improve the detection accuracy when classifying malicious or unauthorized network activity is presented. The algorithm is based on genetic p...
Gianluigi Folino, Clara Pizzuti, Giandomenico Spez...
ACSAC
2003
IEEE
14 years 1 months ago
Intrusion Detection: A Bioinformatics Approach
This paper addresses the problem of detecting masquerading, a security attack in which an intruder assumes the identity of a legitimate user. Many approaches based on Hidden Marko...
Scott E. Coull, Joel W. Branch, Boleslaw K. Szyman...
IEEEIAS
2008
IEEE
14 years 3 months ago
Matrix Factorization Approach for Feature Deduction and Design of Intrusion Detection Systems
Current Intrusion Detection Systems (IDS) examine all data features to detect intrusion or misuse patterns. Some of the features may be redundant or contribute little (if anything...
Václav Snásel, Jan Platos, Pavel Kr&...