{"metadata":{"_oai":{"id":"oai:ipsj.ixsq.nii.ac.jp:00219648","sets":["6164:6165:6640:11008"]},"path":["11008"],"owner":"44499","recid":"219648","title":["脆弱性自動評価システムの継続運用のための再学習手法"],"pubdate":{"attribute_name":"公開日","attribute_value":"2022-07-06"},"_buckets":{"deposit":"468b59aa-5ccd-4c47-aa64-76f77eba6885"},"_deposit":{"id":"219648","pid":{"type":"depid","value":"219648","revision_id":0},"owners":[44499],"status":"published","created_by":44499},"item_title":"脆弱性自動評価システムの継続運用のための再学習手法","author_link":["573077","573079","573078","573074","573080","573076","573075"],"item_titles":{"attribute_name":"タイトル","attribute_value_mlt":[{"subitem_title":"脆弱性自動評価システムの継続運用のための再学習手法"}]},"item_type_id":"18","publish_date":"2022-07-06","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":"神戸大学大学院工学研究科"},{"subitem_text_value":"神戸大学大学院工学研究科／国際電気通信基礎技術研究所"},{"subitem_text_value":"国際電気通信基礎技術研究所"},{"subitem_text_value":"KDDI総合研究所"},{"subitem_text_value":"近畿大学情報学部"},{"subitem_text_value":"神戸大学大学院工学研究科"},{"subitem_text_value":"神戸大学大学院工学研究科"}]},"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/219648/files/IPSJ-DICOMO2022074.pdf","label":"IPSJ-DICOMO2022074.pdf"},"date":[{"dateType":"Available","dateValue":"2024-07-06"}],"format":"application/pdf","billing":["billing_file"],"filename":"IPSJ-DICOMO2022074.pdf","filesize":[{"value":"2.6 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":"44"}],"accessrole":"open_date","version_id":"3045d0c0-0e64-46c2-a2a5-d9684f722cd1","displaytype":"detail","licensetype":"license_note","license_note":"Copyright (c) 2022 by the Information Processing Society of Japan"}]},"item_18_creator_5":{"attribute_name":"著者名","attribute_type":"creator","attribute_value_mlt":[{"creatorNames":[{"creatorName":"Soohyun, Jung"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"白石, 善明"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"小津, 喬"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"橋本, 真幸"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"毛利, 公美"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"葛野, 弘樹"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"森井, 昌克"}],"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":"ソフトウェアの脆弱性が個人や会社などに深刻な損失をもたらす危険がある．脆弱性自動評価の研究でこれまで考慮されていなかったコンセプトドリフトに着目し，脆弱性自動評価の機械学習モデルの性能劣化を低減する再学習手法を提案している．コンセプトドリフトとは，データの統計的な特性が時間や外部要因によって変わることを言う．提案手法は，再学習のタイミングをコンセプトドリフト検知に合わせることで，再学習を行わなかった場合に比べ全体的に高い予測精度となることを確認している．","subitem_description_type":"Other"}]},"item_18_biblio_info_10":{"attribute_name":"書誌情報","attribute_value_mlt":[{"bibliographicPageEnd":"528","bibliographic_titles":[{"bibliographic_title":"マルチメディア，分散，協調とモバイルシンポジウム2022論文集"}],"bibliographicPageStart":"522","bibliographicIssueDates":{"bibliographicIssueDate":"2022-07-06","bibliographicIssueDateType":"Issued"},"bibliographicVolumeNumber":"2022"}]},"relation_version_is_last":true,"weko_creator_id":"44499"},"id":219648,"updated":"2025-01-19T14:49:24.450069+00:00","links":{},"created":"2025-01-19T01:19:42.940165+00:00"}