2026-08-27T04:27:25Z https://meral.edu.mm/oai

oai:meral.edu.mm:recid/4477 2021-12-13T01:58:52Z 1582963302567:1597824273898 user-ucsy

A Network Intrusion Detection Model Using Fuzzy C4.5 Decision Tree Hlaing, Thuzar Khine, May Aye With the growing rate of interconnections among computer systems, reliablenetwork communication is becoming a majorchallenge. Intrusion detection has emerged as asignificant field of research, because it is nottheoretically possible to set up a system with novulnerabilities. This paper purposes the use offuzzy logic to generate decision tree to classifythe intrusion data. Further, the fuzzy decisiontree is then converted to fuzzy rules. The fuzzydecision tree (C4.5) method is used the minimizemeasure of classification ambiguity for differentattributes. This method overcomes the sharpboundary problems; provide good accuracydealing with continuous attributes and predictionproblems. The experimental result is carried outby using 10% KDD Cup 99 benchmark networkintrusion detection dataset. 2012-02-28 http://hdl.handle.net/20.500.12678/0000004477 https://meral.edu.mm/records/4477