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» Applying CMAC-Based On-Line Learning to Intrusion Detection
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NIPS
1997
13 years 6 months ago
Intrusion Detection with Neural Networks
With the rapid expansion of computer networks during the past few years, security has become a crucial issue for modern computer systems. A good way to detect illegitimate use is ...
Jake Ryan, Meng-Jang Lin, Risto Miikkulainen
ISI
2007
Springer
13 years 5 months ago
Host Based Intrusion Detection using Machine Learning
—Detecting unknown malicious code (malcode) is a challenging task. Current common solutions, such as anti-virus tools, rely heavily on prior explicit knowledge of specific instan...
Robert Moskovitch, Shay Pluderman, Ido Gus, Dima S...
GECCO
2004
Springer
121views Optimization» more  GECCO 2004»
13 years 10 months ago
Vulnerability Analysis of Immunity-Based Intrusion Detection Systems Using Evolutionary Hackers
Artificial Immune Systems (AISs) are biologically inspired problem solvers that have been used successfully as intrusion detection systems (IDSs). This paper describes how the des...
Gerry V. Dozier, Douglas Brown, John Hurley, Kryst...
TIFS
2008
154views more  TIFS 2008»
13 years 5 months ago
Data Fusion and Cost Minimization for Intrusion Detection
Abstract--Statistical pattern recognition techniques have recently been shown to provide a finer balance between misdetections and false alarms than the more conventional intrusion...
Devi Parikh, Tsuhan Chen
ASPLOS
2010
ACM
14 years 4 days 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