A hybrid intrusion detection system based on different machine learning algorithms
Recently, Networks have developed quickly during the last many years, and attacks on network infrastructure presently are main threats against network and information security.With quickly growing unauthorized activities in network Intrusion Detection as a part of defense is extremely necessary bec...
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| Main Authors: | , , , |
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| Format: | Conference or Workshop Item |
| Language: | English |
| Published: |
2013
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| Subjects: | |
| Online Access: | http://repo.uum.edu.my/12031/1/PID22.pdf http://repo.uum.edu.my/12031/ http://www.icoci.cms.net.my/proceedings/2013/TOC.html |
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| Summary: | Recently, Networks have developed quickly during the last many years, and attacks on network infrastructure presently are main threats against network and information security.With quickly growing unauthorized activities in network Intrusion Detection as a part of defense is extremely necessary
because traditional firewall techniques cannot provide complete protection
against intrusion. There are numerous study in intrusion detection system (IDS) especially with Genetic algorithms (GA) and Support Vector Machine (SVM) but most of them did
not get the potential of hybrid SVM using GA. Hence this study aims to hybrid GA and forbids
with high accuracy.The paper illustrates
the benefit of hybrid SVM via GA also the paper has proven that by enhancing SVM with GA can reduce false alarms and mean square error (MSE) in detecting intrusion. |
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