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ICCSA
2005
Springer
14 years 3 months ago
M of N Features vs. Intrusion Detection
In order to complement the incomplete training audit trails, model generalization is always utilized to infer more unknown knowledge for intrusion detection. Thus, it is important ...
Zhuowei Li, Amitabha Das
ICONIP
2004
13 years 11 months ago
Hybrid Feature Selection for Modeling Intrusion Detection Systems
Most of the 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 (...
Srilatha Chebrolu, Ajith Abraham, Johnson P. Thoma...
ACSC
2003
IEEE
14 years 3 months ago
Policies for Sharing Distributed Probabilistic Beliefs
In this paper, we present several general policies for deciding when to share probabilistic beliefs between agents for distributed monitoring. In order to evaluate these policies,...
Christopher Leckie, Kotagiri Ramamohanarao
ECBS
2007
IEEE
188views Hardware» more  ECBS 2007»
13 years 11 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...
DBSEC
2001
115views Database» more  DBSEC 2001»
13 years 11 months ago
Randomly roving agents for intrusion detection
Agent based intrusion detection systems IDS have advantages such as scalability, recon gurability, and survivability. In this paper, we introduce a mobile-agent based IDS, called ...
Ira S. Moskowitz, Myong H. Kang, LiWu Chang, Garth...