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» Host Based Intrusion Detection using Machine Learning
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IDEAL
2010
Springer
13 years 6 months ago
Typed Linear Chain Conditional Random Fields and Their Application to Intrusion Detection
Intrusion detection in computer networks faces the problem of a large number of both false alarms and unrecognized attacks. To improve the precision of detection, various machine l...
Carsten Elfers, Mirko Horstmann, Karsten Sohr, Ott...
CNSM
2010
13 years 5 months ago
Effective acquaintance management for Collaborative Intrusion Detection Networks
Abstract--An effective Collaborative Intrusion Detection Network (CIDN) allows distributed Intrusion Detection Systems (IDSes) to collaborate and share their knowledge and opinions...
Carol J. Fung, Jie Zhang, Raouf Boutaba
JCS
2011
138views more  JCS 2011»
12 years 10 months ago
Automatic analysis of malware behavior using machine learning
Malicious software—so called malware—poses a major threat to the security of computer systems. The amount and diversity of its variants render classic security defenses ineffe...
Konrad Rieck, Philipp Trinius, Carsten Willems, Th...
AI
2008
Springer
14 years 2 months ago
Using Unsupervised Learning for Network Alert Correlation
Alert correlation systems are post-processing modules that enable intrusion analysts to find important alerts and filter false positives efficiently from the output of Intrusion...
Reuben Smith, Nathalie Japkowicz, Maxwell Dondo, P...
ICDM
2005
IEEE
187views Data Mining» more  ICDM 2005»
14 years 1 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