{"created":"2023-05-15T08:43:56.545001+00:00","id":9098,"links":{},"metadata":{"_buckets":{"deposit":"1bcf6ce0-dc97-469b-9e29-d7aef0530b06"},"_deposit":{"created_by":13,"id":"9098","owners":[13],"pid":{"revision_id":0,"type":"depid","value":"9098"},"status":"published"},"_oai":{"id":"oai:uec.repo.nii.ac.jp:00009098","sets":["6"]},"author_link":["24787","24788"],"control_number":"9098","item_10001_biblio_info_7":{"attribute_name":"書誌情報","attribute_value_mlt":[{"bibliographicIssueDates":{"bibliographicIssueDate":"2015-05-15","bibliographicIssueDateType":"Issued"},"bibliographicIssueNumber":"5","bibliographicPageEnd":"1387","bibliographicPageStart":"1377","bibliographicVolumeNumber":"56","bibliographic_titles":[{"bibliographic_title":"情報処理学会論文誌","bibliographic_titleLang":"ja"}]}]},"item_10001_description_5":{"attribute_name":"抄録","attribute_value_mlt":[{"subitem_description":"保有している個人に関する情報データベースを他事業者と共有する場合，プライバシへの配慮が必要である．l-多様性等の一般的な匿名化技術では，データベースから個人を特定できる識別子を除外し，擬似識別子（QID）を一般化することで，攻撃者が各個人の属性値を推定することを防ぐ．通常，匿名化は一度のみ行われ，匿名化されたデータベースが複数のデータ利用者に共有され得る．したがって，あるデータ利用者が特に分析を行いたいQIDが完全に一般化されてしまい，まったく分析ができなくなってしまう可能性がある．本研究では，QIDを一般化せず，センシティブ属性にダミーの要素を追加することで，l-多様性を実現する．したがって各データ利用者は，好きなQIDに基づいて自由に分析を行うことが可能となる．提案手法が，既存のl-多様性に関する手法と比べてプライバシと有効性について高いトレードオフを取れることを，実データを用いたシミュレーションによって示す．","subitem_description_type":"Abstract"},{"subitem_description":"Individual privacy needs to be studied when a data holder attempts to share databases containing personal attributes. Existing anonymization techniques remove identifiers and generalize quasi-identifiers (QIDs) from the database. By doing so, adversaries cannot specify each individual's values of the sensitive attributes. Because the database is anonymized based on one-size-fits-all measures in usual, it is possible that QIDs that a data user focuses on are all generalized, and the anonymized database has no value for the user. In this study, we propose a new technique for l-diversity, which keeps QIDs unchanged so that data users can analyze it based on QIDs they focus on. Through simulations of real data sets, we prove that our proposed method can result in a better tradeoff between privacy and utility of the anonymized database.","subitem_description_type":"Abstract"}]},"item_10001_publisher_8":{"attribute_name":"出版者","attribute_value_mlt":[{"subitem_publisher":"情報処理学会"}]},"item_10001_relation_17":{"attribute_name":"関連サイト","attribute_value_mlt":[{"subitem_relation_type_id":{"subitem_relation_type_id_text":"http://id.nii.ac.jp/1001/00142017/","subitem_relation_type_select":"URI"}}]},"item_10001_rights_15":{"attribute_name":"権利","attribute_value_mlt":[{"subitem_rights":"(c) 2015 Information Processing Society of Japan. 本著作物の著作権は情報処理学会に帰属します。本著作物は著作権者である情報処理学会の許可のもとに掲載するものです。ご利用に当たっては「著作権法」ならびに「情報処理学会倫理綱領」に従うことをお願いいたします。"}]},"item_10001_source_id_9":{"attribute_name":"ISSN","attribute_value_mlt":[{"subitem_source_identifier":"18827764","subitem_source_identifier_type":"ISSN"}]},"item_10001_version_type_20":{"attribute_name":"著者版フラグ","attribute_value_mlt":[{"subitem_version_resource":"http://purl.org/coar/version/c_970fb48d4fbd8a85","subitem_version_type":"VoR"}]},"item_creator":{"attribute_name":"著者","attribute_type":"creator","attribute_value_mlt":[{"creatorNames":[{"creatorName":"清, 雄一","creatorNameLang":"ja"},{"creatorName":"セイ, ユウイチ","creatorNameLang":"ja-Kana"},{"creatorName":"Sei, Yuichi","creatorNameLang":"en"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"大須賀, 昭彦","creatorNameLang":"ja"},{"creatorName":"オオスガ, アキヒコ","creatorNameLang":"ja-Kana"},{"creatorName":"Ohsuga, Akihiko","creatorNameLang":"en"}],"nameIdentifiers":[{}]}]},"item_files":{"attribute_name":"ファイル情報","attribute_type":"file","attribute_value_mlt":[{"accessrole":"open_date","date":[{"dateType":"Available","dateValue":"2019-04-09"}],"displaytype":"detail","filename":"IPSJ-JNL5605021.pdf","filesize":[{"value":"932.7 kB"}],"format":"application/pdf","licensetype":"license_note","mimetype":"application/pdf","url":{"label":"IPSJ-JNL5605021","url":"https://uec.repo.nii.ac.jp/record/9098/files/IPSJ-JNL5605021.pdf"},"version_id":"c03c9d8f-1650-47be-ad64-398dd96cabf4"}]},"item_keyword":{"attribute_name":"キーワード","attribute_value_mlt":[{"subitem_subject":"プライバシ","subitem_subject_scheme":"Other"},{"subitem_subject":"データマイニング","subitem_subject_scheme":"Other"},{"subitem_subject":"匿名化","subitem_subject_scheme":"Other"},{"subitem_subject":"privacy","subitem_subject_language":"en","subitem_subject_scheme":"Other"},{"subitem_subject":"data mining","subitem_subject_language":"en","subitem_subject_scheme":"Other"},{"subitem_subject":"anonymization","subitem_subject_language":"en","subitem_subject_scheme":"Other"}]},"item_language":{"attribute_name":"言語","attribute_value_mlt":[{"subitem_language":"jpn"}]},"item_resource_type":{"attribute_name":"資源タイプ","attribute_value_mlt":[{"resourcetype":"journal article","resourceuri":"http://purl.org/coar/resource_type/c_6501"}]},"item_title":"センシティブ属性値のランダムな追加によるl-多様性アルゴリズムの提案","item_titles":{"attribute_name":"タイトル","attribute_value_mlt":[{"subitem_title":"センシティブ属性値のランダムな追加によるl-多様性アルゴリズムの提案","subitem_title_language":"ja"},{"subitem_title":"An Algorithm for l-diversity based on Randomized Addition of Sensitive Values","subitem_title_language":"en"}]},"item_type_id":"10001","owner":"13","path":["6"],"pubdate":{"attribute_name":"PubDate","attribute_value":"2019-04-09"},"publish_date":"2019-04-09","publish_status":"0","recid":"9098","relation_version_is_last":true,"title":["センシティブ属性値のランダムな追加によるl-多様性アルゴリズムの提案"],"weko_creator_id":"13","weko_shared_id":-1},"updated":"2024-03-04T05:07:48.592459+00:00"}