{"_buckets": {"deposit": "dbb7a1f5-b026-49ef-b5b8-9499b3d9def8"}, "_deposit": {"id": "3113", "owners": [], "pid": {"revision_id": 0, "type": "recid", "value": "3113"}, "status": "published"}, "_oai": {"id": "oai:meral.edu.mm:recid/3113", "sets": ["user-ytu"]}, "communities": ["ytu"], "item_1583103067471": {"attribute_name": "Title", "attribute_value_mlt": [{"subitem_1551255647225": "Intrusion Detection System Based on Frequent Pattern Mining", "subitem_1551255648112": "en"}]}, "item_1583103085720": {"attribute_name": "Description", "attribute_value_mlt": [{"interim": "\u003cp\u003e\u0026nbsp;Due\u0026nbsp; to\u0026nbsp; the\u0026nbsp; dramatically\u0026nbsp; increment\u0026nbsp; of\u0026nbsp; internet\u003cbr\u003e\nusage,\u0026nbsp; users\u0026nbsp; are\u0026nbsp; facing\u0026nbsp; various\u0026nbsp; attacks\u0026nbsp; day\u0026nbsp; by\u0026nbsp; day.\u003cbr\u003e\nConsequently, the research area for intrusion detection must\u003cbr\u003e\nbe\u0026nbsp; fresh\u0026nbsp; with\u0026nbsp; new\u0026nbsp; challenges.\u0026nbsp; Intrusion\u0026nbsp; detection\u0026nbsp; system\u003cbr\u003e\nincludes identifying a set of malicious actions that compromise\u003cbr\u003e\nthe\u0026nbsp; integrity,\u0026nbsp; confidentiality,\u0026nbsp; and\u0026nbsp; availability\u0026nbsp; of\u0026nbsp; information\u003cbr\u003e\nresources.\u0026nbsp; The\u0026nbsp; major\u0026nbsp; contribution\u0026nbsp; is\u0026nbsp; to\u0026nbsp; apply\u0026nbsp; data\u0026nbsp; mining\u003cbr\u003e\napproach for network intrusion detection system. Among the\u003cbr\u003e\nseveral features of data\u0026nbsp; mining, association rules\u0026nbsp; mining,FP-\u003cbr\u003e\ngrowth algorithm, is used to find out the frequent itemsets of\u003cbr\u003e\nincoming packets database. Based on these itemsets, anomaly\u003cbr\u003e\ndetection\u0026nbsp; is\u0026nbsp; added.\u0026nbsp; The\u0026nbsp; system\u0026nbsp; will\u0026nbsp; predict\u0026nbsp; whether\u0026nbsp; the\u003cbr\u003e\nincoming data packet is normal or attack. The performance of\u003cbr\u003e\nproposed system is tested by using KDD-99 datasets.\u003c/p\u003e"}]}, "item_1583103108160": {"attribute_name": "Keywords", "attribute_value_mlt": [{"interim": "intrusion detection"}, {"interim": "data mining"}, {"interim": "anomaly"}, {"interim": "algorithm"}, {"interim": "KDD-99 datasets"}]}, "item_1583103120197": {"attribute_name": "Files", "attribute_type": "file", "attribute_value_mlt": [{"accessrole": "open_access", "date": [{"dateType": "Available", "dateValue": "2019-07-04"}], "displaytype": "preview", "download_preview_message": "", "file_order": 0, "filename": "Intrusion Detection System Baed on Frequent Pattern Mining.pdf", "filesize": [{"value": "386 Kb"}], "format": "application/pdf", "future_date_message": "", "is_thumbnail": false, "mimetype": "application/pdf", "size": 386000.0, "url": {"url": "https://meral.edu.mm/record/3113/files/Intrusion Detection System Baed on Frequent Pattern Mining.pdf"}, "version_id": "a0aaf596-503a-46b7-9bb4-37ee9cce7064"}]}, "item_1583103131163": {"attribute_name": "Journal articles", "attribute_value_mlt": [{"subitem_issue": "", "subitem_journal_title": "", "subitem_pages": "", "subitem_volume": ""}]}, "item_1583103147082": {"attribute_name": "Conference papers", "attribute_value_mlt": [{"subitem_acronym": "ICSE", "subitem_c_date": "29-30 December, 2014", "subitem_conference_title": "International Conference on Science and Engineering", "subitem_part": "", "subitem_place": "Myanmar", "subitem_session": "", "subitem_website": ""}]}, "item_1583103211336": {"attribute_name": "Books/reports/chapters", "attribute_value_mlt": [{"subitem_book_title": "", "subitem_isbn": "", "subitem_pages": "", "subitem_place": "", "subitem_publisher": ""}]}, "item_1583103233624": {"attribute_name": "Thesis/dissertations", "attribute_value_mlt": [{"subitem_awarding_university": "", "subitem_supervisor(s)": [{"subitem_supervisor": ""}]}]}, "item_1583105942107": {"attribute_name": "Authors", "attribute_value_mlt": [{"subitem_authors": [{"subitem_authors_fullname": "Myo Min Than"}, {"subitem_authors_fullname": "Nyein Nyein Oo"}, {"subitem_authors_fullname": "Myo Min Than"}]}]}, "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": "2014-12-29"}, "item_1583159847033": {"attribute_name": "Identifier", "attribute_value": "10.5281/zenodo.3268384"}, "item_title": "Intrusion Detection System Based on Frequent Pattern Mining", "item_type_id": "21", "owner": "1", "path": ["1596119372420"], "permalink_uri": "http://hdl.handle.net/20.500.12678/0000003113", "pubdate": {"attribute_name": "Deposited date", "attribute_value": "2019-07-04"}, "publish_date": "2019-07-04", "publish_status": "0", "recid": "3113", "relation": {}, "relation_version_is_last": true, "title": ["Intrusion Detection System Based on Frequent Pattern Mining"], "weko_shared_id": -1}