Abstract
The vast amount of attacks over the Internet makes the computer users and many organizations under potential violation of security. IDS monitor the network to observe suspicious actions going on in a computer or network devices. IDS with using one approach has ability only to detect either misuse or anomaly attacks. This research proposed hybrid IDS by integrated Snort with Naive Bayes to enhance system security to detect attacks. This research used KDD Cup 1999 dataset for test provided hybrid IDS. Accuracy, detection rate, time to build model and false alarm rate used as parameter to measure performance between hybrid Snort with Naïve bayes, Snort with J48graft and Snort with Bayes Net. The result shows that there are slight differences between all the three paradigms
Metadata
Item Type: | Thesis (Masters) |
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Creators: | Creators Email / ID Num. Hussein, Safwan Mawlood UNSPECIFIED |
Contributors: | Contribution Name Email / ID Num. Thesis advisor UNSPECIFIED UNSPECIFIED |
Divisions: | Universiti Teknologi MARA, Shah Alam > Faculty of Computer and Mathematical Sciences |
Programme: | Master of Science in Computer Networking |
Keywords: | Hybird, Attack, Evaluation |
Date: | 2012 |
URI: | https://ir.uitm.edu.my/id/eprint/63971 |
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