{"_buckets": {"deposit": "a750c348-47e3-47f3-bd8b-14215e78800f"}, "_deposit": {"created_by": 45, "id": "6262", "owner": "45", "owners": [45], "owners_ext": {"displayname": "", "username": ""}, "pid": {"revision_id": 0, "type": "recid", "value": "6262"}, "status": "published"}, "_oai": {"id": "oai:meral.edu.mm:recid/6262", "sets": ["user-uit"]}, "communities": ["uit"], "item_1583103067471": {"attribute_name": "Title", "attribute_value_mlt": [{"subitem_1551255647225": "An Analysis of Decision Tree Based Intrusion Detection System", "subitem_1551255648112": "en"}]}, "item_1583103085720": {"attribute_name": "Description", "attribute_value_mlt": [{"interim": "Intrusion detection is the process called indentifying intrusions. The action of entering to a system without permission is called intrusion. With the improving advanced technology of mobile devices such as smart phones, tablet, smart devices, other computing devices, the number of network users are increasing more and more. Hence, security on network is very important for all net consumers. IDS are fundamental part of security boundary. So, they are now considered as a mandatory safety mechanism for critical networks. There are many traditional techniques of intrusion detection. In the research of traditional intrusion detection technology analysis, the statistical model for the establishment of the regulatory basis, management and aggression capability and so on there are still some disadvantages and disabilities, because actual test results cannot meet the requirements. Current methods used in IDS are many. Each method has advantage and disadvantage. Intrusion detection can also be seen as a classification problem. In this research we use K-means and C4.5 algorithms. This paper presents the comparison of intrusion detection by using hybrid data mining methods and a single method. The purpose of this paper is to show the differences of time complexity between hybrid data mining method and a single method. This model is verified using KDD’99 data set. Experimental result clearly shows hybrid methods can reduce model training time while maintaining the higher detection rates than using single method."}]}, "item_1583103108160": {"attribute_name": "Keywords", "attribute_value_mlt": [{"interim": "Intrusion Detection System"}, {"interim": "KDD’99 dataset"}, {"interim": "K-means"}, {"interim": "C4.5"}]}, "item_1583103120197": {"attribute_name": "Files", "attribute_type": "file", "attribute_value_mlt": [{"accessrole": "open_access", "date": [{"dateType": "Available", "dateValue": "2020-11-19"}], "displaytype": "preview", "download_preview_message": "", "file_order": 0, "filename": "An Analysis of Decision Tree Based Intrusion Detection System.pdf", "filesize": [{"value": "1.4 Mb"}], "format": "application/pdf", "future_date_message": "", "is_thumbnail": false, "licensefree": "© 2017 ICAIT", "licensetype": "license_free", "mimetype": "application/pdf", "size": 1400000.0, "url": {"url": "https://meral.edu.mm/record/6262/files/An Analysis of Decision Tree Based Intrusion Detection System.pdf"}, "version_id": "2de008ce-d6aa-4b4f-9ab2-e4b9531be774"}]}, "item_1583103147082": {"attribute_name": "Conference papers", "attribute_value_mlt": [{"subitem_acronym": "ICAIT-2017", "subitem_c_date": "1-2 November, 2017", "subitem_conference_title": "1st International Conference on Advanced Information Technologies", "subitem_place": "Yangon, Myanmar", "subitem_session": "Networking and Network Security", "subitem_website": "https://www.uit.edu.mm/icait-2017/"}]}, "item_1583105942107": {"attribute_name": "Authors", "attribute_value_mlt": [{"subitem_authors": [{"subitem_authors_fullname": "Yi Yi Aung"}, {"subitem_authors_fullname": "Myat Myat Min"}]}]}, "item_1583108359239": {"attribute_name": "Upload type", "attribute_value_mlt": [{"interim": "Publication"}]}, "item_1583108428133": {"attribute_name": "Publication type", "attribute_value_mlt": [{"interim": "Conference paper"}]}, "item_1583159729339": {"attribute_name": "Publication date", "attribute_value": "2017-11-02"}, "item_title": "An Analysis of Decision Tree Based Intrusion Detection System", "item_type_id": "21", "owner": "45", "path": ["1605779935331"], "permalink_uri": "http://hdl.handle.net/20.500.12678/0000006262", "pubdate": {"attribute_name": "Deposited date", "attribute_value": "2020-11-19"}, "publish_date": "2020-11-19", "publish_status": "0", "recid": "6262", "relation": {}, "relation_version_is_last": true, "title": ["An Analysis of Decision Tree Based Intrusion Detection System"], "weko_shared_id": -1}