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» Active learning for network intrusion detection
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CCS
2009
ACM
9 years 10 months ago
Active learning for network intrusion detection
Anomaly detection for network intrusion detection is usually considered an unsupervised task. Prominent techniques, such as one-class support vector machines, learn a hypersphere ...
Nico Görnitz, Marius Kloft, Konrad Rieck, Ulf...
SP
2010
IEEE
187views Security Privacy» more  SP 2010»
9 years 7 months ago
Outside the Closed World: On Using Machine Learning for Network Intrusion Detection
Abstract—In network intrusion detection research, one popular strategy for finding attacks is monitoring a network’s activity for anomalies: deviations from profiles of norma...
Robin Sommer, Vern Paxson
AUSFORENSICS
2004
9 years 5 months ago
Wireless Snort - A WIDS in progress
The Snort intrusion detection system is a widely used and well-regarded open sourcesystem used for the detection of malicious activity in conventional wired networks. Recently, so...
Craig Valli
ECBS
2007
IEEE
188views Hardware» more  ECBS 2007»
9 years 5 months ago
Behavior Analysis-Based Learning Framework for Host Level Intrusion Detection
Machine learning has great utility within the context of network intrusion detection systems. In this paper, a behavior analysis-based learning framework for host level network in...
Haiyan Qiao, Jianfeng Peng, Chuan Feng, Jerzy W. R...
ICAI
2008
9 years 5 months ago
Online Boosting Based Intrusion Detection in Changing Environments
Intrusion detection is an active research field in the development of reliable web-based information systems, where many artificial intelligence techniques are exploited to fit th...
Yanguo Wang, Weiming Hu, Xiaoqin Zhang
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