MERAL Myanmar Education Research and Learning Portal
Item
{"_buckets": {"deposit": "a9bd3c87-89b7-47f3-9885-c94f0a74450c"}, "_deposit": {"id": "4795", "owners": [], "pid": {"revision_id": 0, "type": "recid", "value": "4795"}, "status": "published"}, "_oai": {"id": "oai:meral.edu.mm:recid/4795", "sets": ["user-ucsy"]}, "communities": ["ucsy"], "item_1583103067471": {"attribute_name": "Title", "attribute_value_mlt": [{"subitem_1551255647225": "Analyzing Rules to Detect Attacks in Unauthorized Accesses", "subitem_1551255648112": "en"}]}, "item_1583103085720": {"attribute_name": "Description", "attribute_value_mlt": [{"interim": "Due to increasing incidents of cyber attacks,building effective intrusion detection systems areessential for protecting information systems security,and yet it remains an elusive goal and a great challenge.Current intrusion detection systems (IDS) examine alldata features to detect intrusion or misuse patterns andsome attacks were detected as normal attacks may bevulnerability the whole system. Some of the features maybe redundant or low importance during detectionprocess. This paper utilizes a procedure for analyzingthe attack features and developing rules by combiningsignature analysis with automated techniques toimprove readability, comprehensibility, and maintainabilityof rules. We apply one of the efficient datamining algorithms called random forests for networkintrusion detection. Empirical results prove that theproposed method can get the high accuracy in detectionthe attacks in unauthorized accesses such aswarezmaster attack and buffer overflow attack."}]}, "item_1583103108160": {"attribute_name": "Keywords", "attribute_value_mlt": [{"interim": "relevant features"}, {"interim": "rules"}, {"interim": "intrusion detection"}, {"interim": "warezmaster"}, {"interim": "buffer_overflow"}]}, "item_1583103120197": {"attribute_name": "Files", "attribute_type": "file", "attribute_value": []}, "item_1583103131163": {"attribute_name": "Journal articles", "attribute_value_mlt": [{"subitem_issue": "", "subitem_journal_title": "Eleventh International Conference On Computer Applications (ICCA 2013)", "subitem_pages": "", "subitem_volume": ""}]}, "item_1583103147082": {"attribute_name": "Conference papers", "attribute_value_mlt": [{"subitem_acronym": "", "subitem_c_date": "", "subitem_conference_title": "", "subitem_part": "", "subitem_place": "", "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": "Win, Mya Thidar Myo"}, {"subitem_authors_fullname": "Htun, Phyu Thi"}, {"subitem_authors_fullname": "Khaing, Kyaw Thet"}]}]}, "item_1583108359239": {"attribute_name": "Upload type", "attribute_value_mlt": [{"interim": "Publication"}]}, "item_1583108428133": {"attribute_name": "Publication type", "attribute_value_mlt": [{"interim": "Article"}]}, "item_1583159729339": {"attribute_name": "Publication date", "attribute_value": "2013-02-26"}, "item_1583159847033": {"attribute_name": "Identifier", "attribute_value": "http://onlineresource.ucsy.edu.mm/handle/123456789/690"}, "item_title": "Analyzing Rules to Detect Attacks in Unauthorized Accesses", "item_type_id": "21", "owner": "1", "path": ["1597824273898"], "permalink_uri": "http://hdl.handle.net/20.500.12678/0000004795", "pubdate": {"attribute_name": "Deposited date", "attribute_value": "2019-07-11"}, "publish_date": "2019-07-11", "publish_status": "0", "recid": "4795", "relation": {}, "relation_version_is_last": true, "title": ["Analyzing Rules to Detect Attacks in Unauthorized Accesses"], "weko_shared_id": -1}
Analyzing Rules to Detect Attacks in Unauthorized Accesses
http://hdl.handle.net/20.500.12678/0000004795
http://hdl.handle.net/20.500.12678/0000004795af79b925-fae5-4065-997e-a310d08722fb
a9bd3c87-89b7-47f3-9885-c94f0a74450c
Publication type | ||||||
---|---|---|---|---|---|---|
Article | ||||||
Upload type | ||||||
Publication | ||||||
Title | ||||||
Title | Analyzing Rules to Detect Attacks in Unauthorized Accesses | |||||
Language | en | |||||
Publication date | 2013-02-26 | |||||
Authors | ||||||
Win, Mya Thidar Myo | ||||||
Htun, Phyu Thi | ||||||
Khaing, Kyaw Thet | ||||||
Description | ||||||
Due to increasing incidents of cyber attacks,building effective intrusion detection systems areessential for protecting information systems security,and yet it remains an elusive goal and a great challenge.Current intrusion detection systems (IDS) examine alldata features to detect intrusion or misuse patterns andsome attacks were detected as normal attacks may bevulnerability the whole system. Some of the features maybe redundant or low importance during detectionprocess. This paper utilizes a procedure for analyzingthe attack features and developing rules by combiningsignature analysis with automated techniques toimprove readability, comprehensibility, and maintainabilityof rules. We apply one of the efficient datamining algorithms called random forests for networkintrusion detection. Empirical results prove that theproposed method can get the high accuracy in detectionthe attacks in unauthorized accesses such aswarezmaster attack and buffer overflow attack. | ||||||
Keywords | ||||||
relevant features, rules, intrusion detection, warezmaster, buffer_overflow | ||||||
Identifier | http://onlineresource.ucsy.edu.mm/handle/123456789/690 | |||||
Journal articles | ||||||
Eleventh International Conference On Computer Applications (ICCA 2013) | ||||||
Conference papers | ||||||
Books/reports/chapters | ||||||
Thesis/dissertations |