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A Fast Accurate Network Intrusion Detection System

2013-10-12 08:09:50
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in-depth of computer networks. However,
Intrusion detection systems faces a number of challenges.
One of the important challenge is that, the input data to
be classified is in a high dimension feature space. In this
paper, we effectively proposed PSO-DT intrusion detection
system.Where, Particle Swarm Optimization (PSO) is used as a
feature selection algorithm to maximize the C4.5 Decision Tree
classifier detection accuracy and minimize the timing speed. To
evaluate the performance of the proposed PSO-DT IDS several
experiments on NSL-KDD benchmark network intrusion detec-
tion dataset are conducted. The results obtained demonstrate
the effectiveness of reducing the number of features from 41
to 11, which leads to increase the detection performance to
99.17% and speed up the time to 11.65 sec.
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A849.76 kB2012-11-08|23:52
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