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» Active learning for network intrusion detection
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ISNN
2005
Springer
14 years 3 months ago
Feature Selection and Intrusion Detection Using Hybrid Flexible Neural Tree
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 (if anything)...
Yuehui Chen, Ajith Abraham, Ju Yang
JAIR
2010
181views more  JAIR 2010»
13 years 5 months ago
Intrusion Detection using Continuous Time Bayesian Networks
Intrusion detection systems (IDSs) fall into two high-level categories: network-based systems (NIDS) that monitor network behaviors, and host-based systems (HIDS) that monitor sys...
Jing Xu, Christian R. Shelton
CORR
2010
Springer
123views Education» more  CORR 2010»
13 years 10 months ago
Integrating Innate and Adaptive Immunity for Intrusion Detection
Abstract. Network Intrusion Detection Systems (NIDS) monitor a network with the aim of discerning malicious from benign activity on that network. While a wide range of approaches h...
Gianni Tedesco, Jamie Twycross, Uwe Aickelin
CCS
2003
ACM
14 years 3 months ago
Enhancing byte-level network intrusion detection signatures with context
Many network intrusion detection systems (NIDS) use byte sequences as signatures to detect malicious activity. While being highly efficient, they tend to suffer from a high false...
Robin Sommer, Vern Paxson
CORR
2010
Springer
149views Education» more  CORR 2010»
13 years 10 months ago
Using Rough Set and Support Vector Machine for Network Intrusion Detection
The main function of IDS (Intrusion Detection System) is to protect the system, analyze and predict the behaviors of users. Then these behaviors will be considered an attack or a ...
Rung Ching Chen, Kai-Fan Cheng, Chia-Fen Hsieh