{"id":190584,"updated":"2025-01-20T01:09:16.264983+00:00","links":{},"created":"2025-01-19T00:56:32.670925+00:00","metadata":{"_oai":{"id":"oai:ipsj.ixsq.nii.ac.jp:00190584","sets":["1164:6389:9385:9512"]},"path":["9512"],"owner":"11","recid":"190584","title":["プライバシ保護設定推測における推測値の平行シフトが受容度に与える影響"],"pubdate":{"attribute_name":"公開日","attribute_value":"2018-07-18"},"_buckets":{"deposit":"58e7f2ac-f421-4d6c-8d75-e434a4a1d174"},"_deposit":{"id":"190584","pid":{"type":"depid","value":"190584","revision_id":0},"owners":[11],"status":"published","created_by":11},"item_title":"プライバシ保護設定推測における推測値の平行シフトが受容度に与える影響","author_link":["436511","436506","436510","436508","436504","436509","436503","436505","436507","436512"],"item_titles":{"attribute_name":"タイトル","attribute_value_mlt":[{"subitem_title":"プライバシ保護設定推測における推測値の平行シフトが受容度に与える影響"},{"subitem_title":"Effect of Parallel Shift for User Acceptability in Privacy Setting Prediction","subitem_title_language":"en"}]},"item_type_id":"4","publish_date":"2018-07-18","item_4_text_3":{"attribute_name":"著者所属","attribute_value_mlt":[{"subitem_text_value":"国際電気通信基礎技術研究所(ATR)"},{"subitem_text_value":"明治大学"},{"subitem_text_value":"明治大学"},{"subitem_text_value":"KDDI総合研究所"},{"subitem_text_value":"国際電気通信基礎技術研究所(ATR)"}]},"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/190584/files/IPSJ-SPT18029032.pdf","label":"IPSJ-SPT18029032.pdf"},"date":[{"dateType":"Available","dateValue":"2020-07-18"}],"format":"application/pdf","billing":["billing_file"],"filename":"IPSJ-SPT18029032.pdf","filesize":[{"value":"1.2 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":"46"},{"tax":["include_tax"],"price":"0","billingrole":"44"}],"accessrole":"open_date","version_id":"b1bba6f0-18b0-46ce-8c3d-d0c75389c59b","displaytype":"detail","licensetype":"license_note","license_note":"Copyright (c) 2018 by the Information Processing Society of Japan"}]},"item_4_creator_5":{"attribute_name":"著者名","attribute_type":"creator","attribute_value_mlt":[{"creatorNames":[{"creatorName":"中村, 徹"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"Andrew, A. Adams"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"村田, 潔"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"清本, 晋作"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"鈴木, 信雄"}],"nameIdentifiers":[{}]}]},"item_4_creator_6":{"attribute_name":"著者名(英)","attribute_type":"creator","attribute_value_mlt":[{"creatorNames":[{"creatorName":"Toru, Nakamura","creatorNameLang":"en"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"Andrew, A. Adams","creatorNameLang":"en"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"Kiyoshi, Murata","creatorNameLang":"en"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"Shinsaku, Kiyomoto","creatorNameLang":"en"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"Nobuo, Suzuki","creatorNameLang":"en"}],"nameIdentifiers":[{}]}]},"item_4_source_id_9":{"attribute_name":"書誌レコードID","attribute_value_mlt":[{"subitem_source_identifier":"AA12628305","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":"2188-8671","subitem_source_identifier_type":"ISSN"}]},"item_4_description_7":{"attribute_name":"論文抄録","attribute_value_mlt":[{"subitem_description":"機械学習を用いることで，少数の設定から全体の設定を推測するプライバシ保護設定推測手法が提案されている．少数の設定により全体の設定を推測することで，少ない手間で適切な設定を行うことができる可能性があるが，一方で推測モデルの提供者に悪意があった場合，ユーザが知覚することなく設定を操作される危険性がある．本研究では，通常の推測モデルに加え，プライバシ寄りに推測値をシフトしたモデル，公開寄りに推測値をシフトしたモデル，ランダムに推測値を返すモデルを用いて，それぞれのモデルに対する被験者の受容度について調査を行い，推測モデルの違いが，被験者がモデルの操作について知覚する度合いに与える影響について明らかにした．","subitem_description_type":"Other"}]},"item_4_description_8":{"attribute_name":"論文抄録(英)","attribute_value_mlt":[{"subitem_description":"A machine learning based privacy setting prediction scheme was proposed. The scheme can predict whole adequate settings from the small number of settings. By the scheme, a user can reduce his/her burden for adequate privacy settings. However, there is a potential risk to control users decision about privacy settings without the users' conscious if the model provider is malicious. In this paper, we clarify the effect from manipulating prediction model to participants' recognition by investigating the degree of acceptance with various manipulated prediction models.","subitem_description_type":"Other"}]},"item_4_biblio_info_10":{"attribute_name":"書誌情報","attribute_value_mlt":[{"bibliographicPageEnd":"8","bibliographic_titles":[{"bibliographic_title":"研究報告セキュリティ心理学とトラスト（SPT）"}],"bibliographicPageStart":"1","bibliographicIssueDates":{"bibliographicIssueDate":"2018-07-18","bibliographicIssueDateType":"Issued"},"bibliographicIssueNumber":"32","bibliographicVolumeNumber":"2018-SPT-29"}]},"relation_version_is_last":true,"weko_creator_id":"11"}}