{"updated":"2025-01-19T08:05:02.670873+00:00","metadata":{"_oai":{"id":"oai:ipsj.ixsq.nii.ac.jp:00240105","sets":["6164:6165:7006:11799"]},"path":["11799"],"owner":"44499","recid":"240105","title":["機械学習を用いたネットワーク侵入検知システムにおける攻撃特化型合成モデルの検討"],"pubdate":{"attribute_name":"公開日","attribute_value":"2024-10-23"},"_buckets":{"deposit":"adf53e12-cce1-4798-8503-fb1b13814630"},"_deposit":{"id":"240105","pid":{"type":"depid","value":"240105","revision_id":0},"owners":[44499],"status":"published","created_by":44499},"item_title":"機械学習を用いたネットワーク侵入検知システムにおける攻撃特化型合成モデルの検討","author_link":["658285","658284","658283"],"item_titles":{"attribute_name":"タイトル","attribute_value_mlt":[{"subitem_title":"機械学習を用いたネットワーク侵入検知システムにおける攻撃特化型合成モデルの検討"}]},"item_keyword":{"attribute_name":"キーワード","attribute_value_mlt":[{"subitem_subject":"連合学習，インバランス，特化型，HIKARI-2021，プライバシー保護","subitem_subject_scheme":"Other"}]},"item_type_id":"18","publish_date":"2024-10-23","item_language":{"attribute_name":"言語","attribute_value_mlt":[{"subitem_language":"jpn"}]},"item_18_text_3":{"attribute_name":"著者所属","attribute_value_mlt":[{"subitem_text_value":"福井大学"},{"subitem_text_value":"福井大学"},{"subitem_text_value":"福井大学"}]},"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/240105/files/IPSJ-DPSWS20240039.pdf","label":"IPSJ-DPSWS20240039.pdf"},"date":[{"dateType":"Available","dateValue":"2026-10-23"}],"format":"application/pdf","billing":["billing_file"],"filename":"IPSJ-DPSWS20240039.pdf","filesize":[{"value":"514.1 kB"}],"mimetype":"application/pdf","priceinfo":[{"tax":["include_tax"],"price":"660","billingrole":"5"},{"tax":["include_tax"],"price":"330","billingrole":"6"},{"tax":["include_tax"],"price":"0","billingrole":"34"},{"tax":["include_tax"],"price":"0","billingrole":"44"}],"accessrole":"open_date","version_id":"594bf8b7-51ee-43a4-8fc9-f934b6478888","displaytype":"detail","licensetype":"license_note","license_note":"Copyright (c) 2024 by the Information Processing Society of Japan"}]},"item_18_creator_5":{"attribute_name":"著者名","attribute_type":"creator","attribute_value_mlt":[{"creatorNames":[{"creatorName":"岡田, 明日香"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"川上, 朋也"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"長谷川, 達人"}],"nameIdentifiers":[{}]}]},"item_resource_type":{"attribute_name":"資源タイプ","attribute_value_mlt":[{"resourceuri":"http://purl.org/coar/resource_type/c_5794","resourcetype":"conference paper"}]},"item_18_description_7":{"attribute_name":"論文抄録","attribute_value_mlt":[{"subitem_description":"近年は新しいネットワーク攻撃が日々出現しており，その現状に対応するために機械学習を用いた NIDS の研究が盛んである，一般的に，NIDS において分類する攻撃の種類が多いほど精度が低下する，本論文ではこの点に着目し，特定の攻撃検知に特化した複数のモデルを作成し，それらを組み合わせることによって攻撃の分類を行う手法を提案する，加えて単に多層パーセプトロンを使用して分類を行った場合と比較し，検討手法の評価を行う，","subitem_description_type":"Other"}]},"item_18_biblio_info_10":{"attribute_name":"書誌情報","attribute_value_mlt":[{"bibliographicPageEnd":"235","bibliographic_titles":[{"bibliographic_title":"第32回マルチメディア通信と分散処理ワークショップ論文集"}],"bibliographicPageStart":"234","bibliographicIssueDates":{"bibliographicIssueDate":"2024-10-23","bibliographicIssueDateType":"Issued"}}]},"relation_version_is_last":true,"weko_creator_id":"44499"},"created":"2025-01-19T01:44:06.116433+00:00","id":240105,"links":{}}