{"updated":"2025-01-19T15:20:45.940481+00:00","metadata":{"_oai":{"id":"oai:ipsj.ixsq.nii.ac.jp:00217884","sets":["1164:4088:10830:10908"]},"path":["10908"],"owner":"44499","recid":"217884","title":["深層学習を用いたBGPハイジャックの検知"],"pubdate":{"attribute_name":"公開日","attribute_value":"2022-05-12"},"_buckets":{"deposit":"8479d5ab-8c07-4231-8fae-68939eb92ec5"},"_deposit":{"id":"217884","pid":{"type":"depid","value":"217884","revision_id":0},"owners":[44499],"status":"published","created_by":44499},"item_title":"深層学習を用いたBGPハイジャックの検知","author_link":["565361","565364","565362","565363"],"item_titles":{"attribute_name":"タイトル","attribute_value_mlt":[{"subitem_title":"深層学習を用いたBGPハイジャックの検知"},{"subitem_title":"Detection of BGP hijacking using Deep Learning","subitem_title_language":"en"}]},"item_keyword":{"attribute_name":"キーワード","attribute_value_mlt":[{"subitem_subject":"ICM","subitem_subject_scheme":"Other"}]},"item_type_id":"4","publish_date":"2022-05-12","item_4_text_3":{"attribute_name":"著者所属","attribute_value_mlt":[{"subitem_text_value":"岐阜大学大学院自然科学技術研究科知能理工学専攻"},{"subitem_text_value":"岐阜大学工学部"}]},"item_4_text_4":{"attribute_name":"著者所属(英)","attribute_value_mlt":[{"subitem_text_value":"Graduate School of Engineering, Gifu University","subitem_text_language":"en"},{"subitem_text_value":"Engineering Faculty, Gifu University","subitem_text_language":"en"}]},"item_language":{"attribute_name":"言語","attribute_value_mlt":[{"subitem_language":"jpn"}]},"item_publisher":{"attribute_name":"出版者","attribute_value_mlt":[{"subitem_publisher":"情報処理学会","subitem_publisher_language":"ja"}]},"publish_status":"0","weko_shared_id":-1,"item_file_price":{"attribute_name":"Billing file","attribute_type":"file","attribute_value_mlt":[{"url":{"url":"https://ipsj.ixsq.nii.ac.jp/record/217884/files/IPSJ-IOT22057002.pdf","label":"IPSJ-IOT22057002.pdf"},"format":"application/pdf","billing":["billing_file"],"filename":"IPSJ-IOT22057002.pdf","filesize":[{"value":"1.8 MB"}],"mimetype":"application/pdf","priceinfo":[{"tax":["include_tax"],"price":"0","billingrole":"43"},{"tax":["include_tax"],"price":"0","billingrole":"44"}],"accessrole":"open_login","version_id":"63a1a98d-de18-4616-b46f-ff3e636c1b1c","displaytype":"detail","licensetype":"license_note","license_note":"Copyright (c) 2022 by the Institute of Electronics, Information and Communication Engineers This SIG report is only available to those in membership of the SIG."}]},"item_4_creator_5":{"attribute_name":"著者名","attribute_type":"creator","attribute_value_mlt":[{"creatorNames":[{"creatorName":"中島, 健太"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"原山, 美知子"}],"nameIdentifiers":[{}]}]},"item_4_creator_6":{"attribute_name":"著者名(英)","attribute_type":"creator","attribute_value_mlt":[{"creatorNames":[{"creatorName":"Kenta, Nakashima","creatorNameLang":"en"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"Michiko, Harayama","creatorNameLang":"en"}],"nameIdentifiers":[{}]}]},"item_4_source_id_9":{"attribute_name":"書誌レコードID","attribute_value_mlt":[{"subitem_source_identifier":"AA12326962","subitem_source_identifier_type":"NCID"}]},"item_4_textarea_12":{"attribute_name":"Notice","attribute_value_mlt":[{"subitem_textarea_value":"SIG Technical Reports are nonrefereed and hence may later appear in any journals, conferences, symposia, etc."}]},"item_resource_type":{"attribute_name":"資源タイプ","attribute_value_mlt":[{"resourceuri":"http://purl.org/coar/resource_type/c_18gh","resourcetype":"technical report"}]},"item_4_source_id_11":{"attribute_name":"ISSN","attribute_value_mlt":[{"subitem_source_identifier":"2188-8787","subitem_source_identifier_type":"ISSN"}]},"item_4_description_7":{"attribute_name":"論文抄録","attribute_value_mlt":[{"subitem_description":"大規模な Autonomous System (AS）の障害やネットワーク攻撃による被害の発生は，Border  Gateway Protocol（BGP）のメッセージに影響を与え，インターネット通信全体の遅延や不安定化などをもたらす．本研究ではこれを BGP ハイジャックと捉え，深層学習を用いた BGP メッセージの異常検知を提案する．本報告では Malaysia-Telekom, Level3, Google, Facebook に起因する 4 つのインシデントを取り上げ，インシデントの発生周辺期間の BGP メッセージを解析して ASpath 長の統計値など９つの特徴量を求めた．これを Multilayer Perceptron (MLP)  に学習させインシデントの検知精度を求めた．その結果，新規 Announce や Withdraw などいくつかの特徴量はインシデントに連動した変化が観察された．また，Malaysia-Telekom と Level3 のインシデントについては一定の検知精度が得られた．本報告では，BGP メッセージの特徴量の解析方法，特徴量の変化を示し，本手法による異常検知性能を検証する．","subitem_description_type":"Other"}]},"item_4_description_8":{"attribute_name":"論文抄録(英)","attribute_value_mlt":[{"subitem_description":"Failures of large autonomous systems (ASs) and network attacks can affect Border Gateway Protocol (BGP) messages, causing delays and instability in overall Internet communications. We note this as BGP hijacking and propose an anomaly detection method for BGP messages using deep learning. We report four incidents caused by Malaysia-Telekom, Level3, Google, and Facebook. We analyze BGP messages around the incidents to obtain nine features, such as AS path length statistics. These were trained on a multilayer perceptron (MLP) to determine the accuracy of incident detection. As a result, some of the features, such as new BGP announcements and withdrawals, change in conjunction with incidents. Detection accuracies for Malaysia-Telekom and Level 3 incidents were high. In this report, we show how to analyze the features of BGP messages, how they change, and the anomaly detection performance of our method.","subitem_description_type":"Other"}]},"item_4_biblio_info_10":{"attribute_name":"書誌情報","attribute_value_mlt":[{"bibliographicPageEnd":"6","bibliographic_titles":[{"bibliographic_title":"研究報告インターネットと運用技術（IOT）"}],"bibliographicPageStart":"1","bibliographicIssueDates":{"bibliographicIssueDate":"2022-05-12","bibliographicIssueDateType":"Issued"},"bibliographicIssueNumber":"2","bibliographicVolumeNumber":"2022-IOT-57"}]},"relation_version_is_last":true,"weko_creator_id":"44499"},"created":"2025-01-19T01:18:18.656422+00:00","id":217884,"links":{}}