2024-03-28T13:56:13Z
https://meral.edu.mm/oai
oai:meral.edu.mm:recid/3113
2021-12-13T05:46:30Z
1582963413512:1596119372420
user-ytu
Intrusion Detection System Based on Frequent Pattern Mining
Myo Min Than
Nyein Nyein Oo
Myo Min Than
<p> Due to the dramatically increment of internet<br>
usage, users are facing various attacks day by day.<br>
Consequently, the research area for intrusion detection must<br>
be fresh with new challenges. Intrusion detection system<br>
includes identifying a set of malicious actions that compromise<br>
the integrity, confidentiality, and availability of information<br>
resources. The major contribution is to apply data mining<br>
approach for network intrusion detection system. Among the<br>
several features of data mining, association rules mining,FP-<br>
growth algorithm, is used to find out the frequent itemsets of<br>
incoming packets database. Based on these itemsets, anomaly<br>
detection is added. The system will predict whether the<br>
incoming data packet is normal or attack. The performance of<br>
proposed system is tested by using KDD-99 datasets.</p>
2014-12-29
http://hdl.handle.net/20.500.12678/0000003113
https://meral.edu.mm/records/3113