{"_buckets": {"deposit": "0aaf926a-c897-4efd-9079-251ccd7ca47d"}, "_deposit": {"id": "4549", "owners": [], "pid": {"revision_id": 0, "type": "recid", "value": "4549"}, "status": "published"}, "_oai": {"id": "oai:meral.edu.mm:recid/4549", "sets": ["user-ucsy"]}, "communities": ["ucsy"], "item_1583103067471": {"attribute_name": "Title", "attribute_value_mlt": [{"subitem_1551255647225": "Flooding Attack Detection and Mitigation in Software-Defined Networking", "subitem_1551255648112": "en"}]}, "item_1583103085720": {"attribute_name": "Description", "attribute_value_mlt": [{"interim": "Flooding attack is a network attack that sends a large amount of traffic to thevictim networks or services with the aim of causing denial-of-service. In SoftwareDefined Networking (SDN) environment, this attack might not only breach the hostsand services but also the SDN controller. Besides, it will also cause disconnection oflinks between the controller and the switches. Thus, an effective detection andmitigation technique of flooding attack is required. Statistical analysis techniques arewidely used for detection and mitigation of flooding attack. However, theeffectiveness of these techniques strongly depends on the defined threshold. Definingthe static threshold is a tedious job and most of the time produces a high false positivealarm. In this system, we proposed the dynamic threshold which is calculated usingModified Adaptive Threshold Algorithm (MATA). The original Adaptive ThresholdAlgorithm (ATA) is based on the Exponential Weighted Moving Average (EWMA)formula which produces high number of false alarms. To reduce the false alarms, thealarm signal will only be generated after a minimum number of consecutive violationsof the threshold. This however has increased the false negative rate when the networkis under attack. In order to reduce this false negative rate, MATA adapted the baselinetraffic information of the network infrastructure. The comparative analysis of MATAand ATA is performed through the measurement of false negative rate, and accuracyof detection rate. The experimental results show that MATA is able to reduce falsenegative rate up to 17.74% and increase the detection accuracy of 16.11% over thevarious types of flooding attacks at the transport layer."}]}, "item_1583103108160": {"attribute_name": "Keywords", "attribute_value": []}, "item_1583103120197": {"attribute_name": "Files", "attribute_type": "file", "attribute_value_mlt": [{"accessrole": "open_access", "date": [{"dateType": "Available", "dateValue": "2020-01-14"}], "displaytype": "preview", "download_preview_message": "", "file_order": 0, "filename": "Research Book [Nan Haymarn Oo].pdf", "filesize": [{"value": "2857 Kb"}], "format": "application/pdf", "future_date_message": "", "is_thumbnail": false, "licensetype": "license_free", "mimetype": "application/pdf", "size": 2857000.0, "url": {"url": "https://meral.edu.mm/record/4549/files/Research Book [Nan Haymarn Oo].pdf"}, "version_id": "a26da070-fa6e-42f6-b4dd-8c3f432d8691"}]}, "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": "", "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": "University of Computer Studies, Yangon", "subitem_supervisor(s)": [{"subitem_supervisor": ""}]}]}, "item_1583105942107": {"attribute_name": "Authors", "attribute_value_mlt": [{"subitem_authors": [{"subitem_authors_fullname": "Oo, Nan Haymarn"}]}]}, "item_1583108359239": {"attribute_name": "Upload type", "attribute_value_mlt": [{"interim": "Publication"}]}, "item_1583108428133": {"attribute_name": "Publication type", "attribute_value_mlt": [{"interim": "Thesis"}]}, "item_1583159729339": {"attribute_name": "Publication date", "attribute_value": "2019-10"}, "item_1583159847033": {"attribute_name": "Identifier", "attribute_value": "http://onlineresource.ucsy.edu.mm/handle/123456789/2471"}, "item_title": "Flooding Attack Detection and Mitigation in Software-Defined Networking", "item_type_id": "21", "owner": "1", "path": ["1597824322519"], "permalink_uri": "http://hdl.handle.net/20.500.12678/0000004549", "pubdate": {"attribute_name": "Deposited date", "attribute_value": "2020-01-14"}, "publish_date": "2020-01-14", "publish_status": "0", "recid": "4549", "relation": {}, "relation_version_is_last": true, "title": ["Flooding Attack Detection and Mitigation in Software-Defined Networking"], "weko_shared_id": -1}