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» Combined Data Mining Approach for Intrusion Detection
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CORR
2010
Springer
143views Education» more  CORR 2010»
13 years 8 months ago
Dendritic Cells for Anomaly Detection
Artificial immune systems, more specifically the negative selection algorithm, have previously been applied to intrusion detection. The aim of this research is to develop an intrus...
Julie Greensmith, Jamie Twycross, Uwe Aickelin
IJAIT
2007
180views more  IJAIT 2007»
13 years 8 months ago
Detection and Prediction of Rare Events in Transaction Databases
Rare events analysis is an area that includes methods for the detection and prediction of events, e.g. a network intrusion or an engine failure, that occur infrequently and have s...
Christos Berberidis, Ioannis P. Vlahavas
ACSAC
2003
IEEE
14 years 10 days ago
Bayesian Event Classification for Intrusion Detection
Intrusion detection systems (IDSs) attempt to identify attacks by comparing collected data to predefined signatures known to be malicious (misuse-based IDSs) or to a model of lega...
Christopher Krügel, Darren Mutz, William K. R...
ASPLOS
2010
ACM
14 years 3 months ago
Accelerating the local outlier factor algorithm on a GPU for intrusion detection systems
The Local Outlier Factor (LOF) is a very powerful anomaly detection method available in machine learning and classification. The algorithm defines the notion of local outlier in...
Malak Alshawabkeh, Byunghyun Jang, David R. Kaeli
ECAI
2010
Springer
13 years 8 months ago
Mining Outliers with Adaptive Cutoff Update and Space Utilization (RACAS)
Recently the efficiency of an outlier detection algorithm ORCA was improved by RCS (Randomization with faster Cutoff update and Space utilization after pruning), which changes the ...
Chi-Cheong Szeto, Edward Hung