{"links":{},"metadata":{"_oai":{"id":"oai:ipsj.ixsq.nii.ac.jp:00227108","sets":["1164:1579:11081:11309"]},"path":["11309"],"owner":"44499","recid":"227108","title":["FPGA上での軽量オンデバイス学習を用いた高帯域ネットワーク侵入検知手法"],"pubdate":{"attribute_name":"公開日","attribute_value":"2023-07-27"},"_buckets":{"deposit":"48b8db87-2356-43d4-b0e3-f192ce13b5d1"},"_deposit":{"id":"227108","pid":{"type":"depid","value":"227108","revision_id":0},"owners":[44499],"status":"published","created_by":44499},"item_title":"FPGA上での軽量オンデバイス学習を用いた高帯域ネットワーク侵入検知手法","author_link":["604512","604511"],"item_titles":{"attribute_name":"タイトル","attribute_value_mlt":[{"subitem_title":"FPGA上での軽量オンデバイス学習を用いた高帯域ネットワーク侵入検知手法"}]},"item_keyword":{"attribute_name":"キーワード","attribute_value_mlt":[{"subitem_subject":"スマートNIC・エッジコンピューティング基盤","subitem_subject_scheme":"Other"}]},"item_type_id":"4","publish_date":"2023-07-27","item_4_text_3":{"attribute_name":"著者所属","attribute_value_mlt":[{"subitem_text_value":"慶應義塾大学理工学研究科"},{"subitem_text_value":"慶應義塾大学理工学研究科"}]},"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/227108/files/IPSJ-ARC23254031.pdf","label":"IPSJ-ARC23254031.pdf"},"date":[{"dateType":"Available","dateValue":"2025-07-27"}],"format":"application/pdf","billing":["billing_file"],"filename":"IPSJ-ARC23254031.pdf","filesize":[{"value":"2.8 MB"}],"mimetype":"application/pdf","priceinfo":[{"tax":["include_tax"],"price":"660","billingrole":"5"},{"tax":["include_tax"],"price":"330","billingrole":"6"},{"tax":["include_tax"],"price":"0","billingrole":"16"},{"tax":["include_tax"],"price":"0","billingrole":"44"}],"accessrole":"open_date","version_id":"0f468cd3-94ef-4a52-80a9-503befbd99cc","displaytype":"detail","licensetype":"license_note","license_note":"Copyright (c) 2023 by the Information Processing Society of Japan"}]},"item_4_creator_5":{"attribute_name":"著者名","attribute_type":"creator","attribute_value_mlt":[{"creatorNames":[{"creatorName":"呉, 漫"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"近藤, 正章"}],"nameIdentifiers":[{}]}]},"item_4_source_id_9":{"attribute_name":"書誌レコードID","attribute_value_mlt":[{"subitem_source_identifier":"AN10096105","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":"2188-8574","subitem_source_identifier_type":"ISSN"}]},"item_4_description_7":{"attribute_name":"論文抄録","attribute_value_mlt":[{"subitem_description":"機械学習を利用したネットワーク侵入検出システム（NIDS）により，複雑化するネットワークトラフィックに対して効率的にセキュリティ上の侵入検知が可能になる．しかし，大規模なニューラルネットワークを用いた NIDS を効果的，かつ高帯域に実現することは，ニューラルネットワーク自体の演算負荷と特徴量抽出にかかる負荷の点で簡単ではない．そこで，本稿ではネットワーク環境のダイナミックさや新たに登場するセキュリティ上の脅威に適応するために，オンラインモデル更新をサポートしつつ，高帯域のトラフィックに対してリアルタイムに NIDS が可能なアプローチを検討する．まず，従来 NIDS で利用されてきた統計的特徴量を，パケットのバイト列から返還することのなく直接抽出する手法を検討する．さらに，既存のオンデバイス逐次学習手法を利用した異常検知手法を用いて軽量のオンライン NIDS の構築を目指す．本システムを FPGA を搭載した SmartNIC 上に実装し，CIC-IDS2018 データセットを用いて評価した．評価の結果，0.986 以上の AUC スコアを維持しながら，最大 39.62Gbps の検出スループットを達成できることがわかった．","subitem_description_type":"Other"}]},"item_4_biblio_info_10":{"attribute_name":"書誌情報","attribute_value_mlt":[{"bibliographicPageEnd":"7","bibliographic_titles":[{"bibliographic_title":"研究報告システム・アーキテクチャ（ARC）"}],"bibliographicPageStart":"1","bibliographicIssueDates":{"bibliographicIssueDate":"2023-07-27","bibliographicIssueDateType":"Issued"},"bibliographicIssueNumber":"31","bibliographicVolumeNumber":"2023-ARC-254"}]},"relation_version_is_last":true,"weko_creator_id":"44499"},"created":"2025-01-19T01:26:25.356000+00:00","updated":"2025-01-19T12:16:28.950037+00:00","id":227108}