{"updated":"2025-01-20T02:20:25.340266+00:00","metadata":{"_oai":{"id":"oai:ipsj.ixsq.nii.ac.jp:00187283","sets":["6164:6165:6462:9463"]},"path":["9463"],"owner":"11","recid":"187283","title":["加法準同型暗号を用いたプライバシー保護Extreme Learning Machine"],"pubdate":{"attribute_name":"公開日","attribute_value":"2017-10-16"},"_buckets":{"deposit":"ac7d169a-f96b-431b-a6eb-465d41b5ba78"},"_deposit":{"id":"187283","pid":{"type":"depid","value":"187283","revision_id":0},"owners":[11],"status":"published","created_by":11},"item_title":"加法準同型暗号を用いたプライバシー保護Extreme Learning Machine","author_link":["423111","423117","423119","423115","423122","423109","423112","423116","423118","423121","423124","423110","423114","423113","423123","423120"],"item_titles":{"attribute_name":"タイトル","attribute_value_mlt":[{"subitem_title":"加法準同型暗号を用いたプライバシー保護Extreme Learning Machine"},{"subitem_title":"Privacy Preserving Extreme Learning Machine Using Additively Homomorphic Encryption","subitem_title_language":"en"}]},"item_keyword":{"attribute_name":"キーワード","attribute_value_mlt":[{"subitem_subject":"PWS,機械学習,加法準同型暗号,識別器,ニューラルネット","subitem_subject_scheme":"Other"}]},"item_type_id":"18","publish_date":"2017-10-16","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電気電子工学専攻"},{"subitem_text_value":"神戸大学大学院工学研究科電気電子工学専攻/国立研究開発法人情報通信研究機構"},{"subitem_text_value":"神戸大学大学院工学研究科電気電子工学専攻"},{"subitem_text_value":"神戸大学大学院工学研究科電気電子工学専攻"},{"subitem_text_value":"国立研究開発法人情報通信研究機構"},{"subitem_text_value":"国立研究開発法人情報通信研究機構"},{"subitem_text_value":"国立研究開発法人情報通信研究機構"},{"subitem_text_value":"国立研究開発法人情報通信研究機構"}]},"item_18_text_4":{"attribute_name":"著者所属(英)","attribute_value_mlt":[{"subitem_text_value":"Department of Electrical and Electronic Engineering, Graduate School of Engineering, Kobe University","subitem_text_language":"en"},{"subitem_text_value":"Department of Electrical and Electronic Engineering, Graduate School of Engineering, Kobe University / National Institute of Information and Communications Technology","subitem_text_language":"en"},{"subitem_text_value":"Department of Electrical and Electronic Engineering, Graduate School of Engineering, Kobe University","subitem_text_language":"en"},{"subitem_text_value":"Department of Electrical and Electronic Engineering, Graduate School of Engineering, Kobe University","subitem_text_language":"en"},{"subitem_text_value":"National Institute of Information and Communications Technology","subitem_text_language":"en"},{"subitem_text_value":"National Institute of Information and Communications Technology","subitem_text_language":"en"},{"subitem_text_value":"National Institute of Information and Communications Technology","subitem_text_language":"en"},{"subitem_text_value":"National Institute of Information and Communications Technology","subitem_text_language":"en"}]},"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/187283/files/IPSJCSS2017108.pdf","label":"IPSJCSS2017108.pdf"},"date":[{"dateType":"Available","dateValue":"2017-10-16"}],"format":"application/pdf","billing":["billing_file"],"filename":"IPSJCSS2017108.pdf","filesize":[{"value":"469.4 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":"30"},{"tax":["include_tax"],"price":"0","billingrole":"46"},{"tax":["include_tax"],"price":"0","billingrole":"44"}],"accessrole":"open_date","version_id":"0d70cc0c-8825-4a0e-822b-f16149ce07b8","displaytype":"detail","licensetype":"license_note","license_note":"Copyright (c) 2017 by the Information Processing Society of Japan"}]},"item_18_creator_5":{"attribute_name":"著者名","attribute_type":"creator","attribute_value_mlt":[{"creatorNames":[{"creatorName":"栗, 昌平"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"林, 卓也"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"大森, 敏明"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"小澤, 誠一"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"青野, 良範"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"Le, Trieu Phong"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"王, 立華"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"盛合, 志帆"}],"nameIdentifiers":[{}]}]},"item_18_creator_6":{"attribute_name":"著者名(英)","attribute_type":"creator","attribute_value_mlt":[{"creatorNames":[{"creatorName":"Shohei, Kuri","creatorNameLang":"en"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"Takuya, Hayashi","creatorNameLang":"en"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"Toshiaki, Omori","creatorNameLang":"en"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"Seiichi, Ozawa","creatorNameLang":"en"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"Yoshinori, Aono","creatorNameLang":"en"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"Le, Trieu Phong","creatorNameLang":"en"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"Lihua, Wang","creatorNameLang":"en"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"Shiho, Moriai","creatorNameLang":"en"}],"nameIdentifiers":[{}]}]},"item_18_relation_9":{"attribute_name":"書誌レコードID","attribute_value_mlt":[{"subitem_relation_type_id":{"subitem_relation_type_select":"NCID","subitem_relation_type_id_text":"ISSN 1882-0840"}}]},"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":"本稿では,加法準同型暗号を用いたプライバシー保護を可能とするニューラルネットモデルExtreme Learning Machine (ELM)を提案する.提案手法では,データ漏洩リスク無しにデータ解析のための代理計算サーバーの利用が可能となる. ベンチマークデータを用いた性能評価実験では,ロジスティック回帰との比較を行い,提案したELMは分類精度で優れた性能(最大で12%向上)をもつことを示した.提案手法は,プライバシー保護を可能としながら非線形分類器としての高い分類精度を示し,個人情報を含むデータのクラウドサーバー上でのデータ解析を促進するものと期待される.","subitem_description_type":"Other"}]},"item_18_description_8":{"attribute_name":"論文抄録(英)","attribute_value_mlt":[{"subitem_description":"We propose a privacy preserving Extreme Learning Machine (PP-ELM) using additively homo-morphic encryption. We consider a three participants model; data contributors, an outsourced server, and a data analyst. The data contributor preprocesses the data and encrypts it with additively homomorphic encryption. The outsourced server receives the encrypted data and performs summation on the encrypted data. The data analyst receives the summation from the outsourced server and decrypts it, then uses it to obtain an optimized parameter of ELM. The proposed outsourcing model is expected to mitigate a hurdle of personal data usage on a cloud service.","subitem_description_type":"Other"}]},"item_18_biblio_info_10":{"attribute_name":"書誌情報","attribute_value_mlt":[{"bibliographic_titles":[{"bibliographic_title":"コンピュータセキュリティシンポジウム2017論文集"}],"bibliographicIssueDates":{"bibliographicIssueDate":"2017-10-16","bibliographicIssueDateType":"Issued"},"bibliographicIssueNumber":"2","bibliographicVolumeNumber":"2017"}]},"relation_version_is_last":true,"weko_creator_id":"11"},"created":"2025-01-19T00:53:58.023601+00:00","id":187283,"links":{}}