{"_buckets": {"deposit": "d08a3498-c07b-4a91-a865-9720f86c05db"}, "_deposit": {"id": "4899", "owners": [], "pid": {"revision_id": 0, "type": "recid", "value": "4899"}, "status": "published"}, "_oai": {"id": "oai:meral.edu.mm:recid/4899", "sets": ["user-ucsy"]}, "communities": ["ucsy"], "item_1583103067471": {"attribute_name": "Title", "attribute_value_mlt": [{"subitem_1551255647225": "Proposed ApplicableFramework for Extracting Rootkits Features and Clustering through Dynamic Analysis for Incident Handling Systems", "subitem_1551255648112": "en"}]}, "item_1583103085720": {"attribute_name": "Description", "attribute_value_mlt": [{"interim": "Today’s threats have become complex multi-modulesystems using sophisticated techniques to target andattack vulnerable systems. The use of rootkits androotkit technologies in malware and cybercrime isincreasing. To remain undetected, malware creatorsincorporate rootkit components to maximize theirstealth capabilities. The main reason to develop thisresearch is the longer the malware can remainundetected on a compromised machine, the more thecybercriminal can profit. Therefore, the proposedsystem will focus on analyzing the kernel and user levelrootkits based on Window operating system withCuckoo sandbox. This system performs automated andmanual analysis for ensuring the important of theircharacteristics. The objectives are to identify therootkits based on their natures and complexity, and topropose feature extraction algorithm for improving thedetection model.Effective MalwareFeature ExtractionAlgorithm(EMFEA) is proposed in this framework fordetecting the future malware in Incident HandlingSystems. Moreover, the proposed system categorizesthe rootkits based on their relevant and prominentfeatures by using Hierarchical Clustering algorithm inWEKA."}]}, "item_1583103108160": {"attribute_name": "Keywords", "attribute_value_mlt": [{"interim": "Rootkit"}, {"interim": "feature extraction"}, {"interim": "Hierarchical Clustering"}]}, "item_1583103120197": {"attribute_name": "Files", "attribute_type": "file", "attribute_value_mlt": [{"accessrole": "open_access", "date": [{"dateType": "Available", "dateValue": "2019-07-12"}], "displaytype": "preview", "download_preview_message": "", "file_order": 0, "filename": "proceeding_total-pages-342-350.pdf", "filesize": [{"value": "3373 Kb"}], "format": "application/pdf", "future_date_message": "", "is_thumbnail": false, "licensetype": "license_free", "mimetype": "application/pdf", "size": 3373000.0, "url": {"url": "https://meral.edu.mm/record/4899/files/proceeding_total-pages-342-350.pdf"}, "version_id": "3b9a7d8c-f93e-43be-9820-eddb0857c125"}]}, "item_1583103131163": {"attribute_name": "Journal articles", "attribute_value_mlt": [{"subitem_issue": "", "subitem_journal_title": "Fifteenth International Conference on Computer Applications(ICCA 2017)", "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": "San, Cho Cho"}, {"subitem_authors_fullname": "Thwin, Mie Mie Su"}]}]}, "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": "2017-02-16"}, "item_1583159847033": {"attribute_name": "Identifier", "attribute_value": "http://onlineresource.ucsy.edu.mm/handle/123456789/802"}, "item_title": "Proposed ApplicableFramework for Extracting Rootkits Features and Clustering through Dynamic Analysis for Incident Handling Systems", "item_type_id": "21", "owner": "1", "path": ["1597824273898"], "permalink_uri": "http://hdl.handle.net/20.500.12678/0000004899", "pubdate": {"attribute_name": "Deposited date", "attribute_value": "2019-07-12"}, "publish_date": "2019-07-12", "publish_status": "0", "recid": "4899", "relation": {}, "relation_version_is_last": true, "title": ["Proposed ApplicableFramework for Extracting Rootkits Features and Clustering through Dynamic Analysis for Incident Handling Systems"], "weko_shared_id": -1}