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» A Labeled Data Set for Flow-Based Intrusion Detection
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CSFW
2004
IEEE
13 years 8 months ago
Using Active Learning in Intrusion Detection
Intrusion Detection Systems (IDSs) have become an important part of operational computer security. They are the last line of defense against malicious hackers and help detect ongo...
Magnus Almgren, Erland Jonsson
RSP
2007
IEEE
158views Control Systems» more  RSP 2007»
13 years 11 months ago
SPP-NIDS - A Sea of Processors Platform for Network Intrusion Detection Systems
A widely used approach to avoid network intrusion is SNORT, an open source Network Intrusion Detection System (NIDS). This work describes SPP-NIDS, a architecture for intrusion de...
Luis Carlos Caruso, Guilherme Guindani, Hugo Schmi...
KDD
2008
ACM
140views Data Mining» more  KDD 2008»
14 years 5 months ago
Semi-supervised approach to rapid and reliable labeling of large data sets
Supervised classification methods have been shown to be very effective for a large number of applications. They require a training data set whose instances are labeled to indicate...
György J. Simon, Vipin Kumar, Zhi-Li Zhang
JSS
2002
198views more  JSS 2002»
13 years 4 months ago
Automated discovery of concise predictive rules for intrusion detection
This paper details an essential component of a multi-agent distributed knowledge network system for intrusion detection. We describe a distributed intrusion detection architecture...
Guy G. Helmer, Johnny S. Wong, Vasant Honavar, Les...
ICNC
2005
Springer
13 years 10 months ago
Applying Genetic Programming to Evolve Learned Rules for Network Anomaly Detection
The DARPA/MIT Lincoln Laboratory off-line intrusion detection evaluation data set is the most widely used public benchmark for testing intrusion detection systems. But the presence...
Chuanhuan Yin, Shengfeng Tian, Houkuan Huang, Jun ...