{"created":"2023-05-15T08:43:56.295421+00:00","id":9092,"links":{},"metadata":{"_buckets":{"deposit":"8faebd5b-7045-44a3-82e8-892667b9a95e"},"_deposit":{"created_by":13,"id":"9092","owners":[13],"pid":{"revision_id":0,"type":"depid","value":"9092"},"status":"published"},"_oai":{"id":"oai:uec.repo.nii.ac.jp:00009092","sets":["6"]},"author_link":["24288","24290"],"control_number":"9092","item_10001_biblio_info_7":{"attribute_name":"書誌情報","attribute_value_mlt":[{"bibliographicIssueDates":{"bibliographicIssueDate":"2014-05-01","bibliographicIssueDateType":"Issued"},"bibliographicIssueNumber":"5","bibliographicPageEnd":"963","bibliographicPageStart":"953","bibliographicVolumeNumber":"J97-D","bibliographic_titles":[{"bibliographic_title":"電子情報通信学会論文誌. D, 情報・システム","bibliographic_titleLang":"ja"}]}]},"item_10001_description_5":{"attribute_name":"抄録","attribute_value_mlt":[{"subitem_description":"ユーザがカテゴリー化された自身のデータを改変してサーバに送信し，サーバは得た情報から統計的な解析を行う，というプライバシー保護モデルを実現するRandomized Responseスキームが提案されている．サーバ側は受け取った情報から，各カテゴリーに属すユーザ数の真の分布を推測する．各ユーザの真のカテゴリーがどのカテゴリーに改変されてサーバへ送信されるかは，あらかじめ設定された確率行列に基づいて決定される．確率行列の値を変更することで，異なるプライバシー保護レベルを実現できる．また，プライバシー保護レベルと，サーバにおける推測誤差とはトレードオフの関係にある．従来は，全ユーザが同一の確率行列を利用する状況のみが想定されており，ユーザごとにプライバシー保護レベルを変えることができないという制約があった．本論文では，ユーザごとに異なる確率行列を利用するモデルを提案する．異なる確率行列が利用される場合，サーバ側において各カテゴリーに属すユーザ数の分布を推測する手法は確立されていない．本論文では推測誤差を定量的に取扱い，最も確からしいユーザ数の分布を推測する手法を提案する．従来手法と比較してサーバ側での推測誤差を70%程度削減できることを，数学的解析及び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":"Randomized Response Scheme (RR) can realize a privacy-preserving model where each user replaces his original category of his data to another category probabilistically. Each user then sends the replaced category to a server which analyzes the collected data and estimates the distribution of the original categories. The replacement of categories depends on a probabilistic matrix. The level of privacy can be adjusted by changing values of the probability matrix, and there is a tradeoff between the amount of the estimated error at the server and the level of privacy. Existing studies assume that all users use the same probability matrix, so they cannot change the level of privacy depending on each user's demand. In this paper, we propose a model where users can use different probabilistic matrix. Existing studies cannot estimate the distribution of original categories in the situation where different probabilistic matrixes are used. We provide quantitative analysis of the estimated errors and propose a method to estimate the distribution by a maximum likelihood estimate. By mathematical analysis and simulations, we prove our proposed method can reduce the estimated errors by approximately 70%.","subitem_description_type":"Abstract"}]},"item_10001_publisher_8":{"attribute_name":"出版者","attribute_value_mlt":[{"subitem_publisher":"電子情報通信学会"}]},"item_10001_relation_17":{"attribute_name":"関連サイト","attribute_value_mlt":[{"subitem_relation_type_id":{"subitem_relation_type_id_text":"http://search.ieice.org/index.html","subitem_relation_type_select":"URI"}}]},"item_10001_rights_15":{"attribute_name":"権利","attribute_value_mlt":[{"subitem_rights":"Copyright © 2014 IEICE"}]},"item_10001_source_id_9":{"attribute_name":"ISSN","attribute_value_mlt":[{"subitem_source_identifier":"1881-0225","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":"j97-d_5_953.pdf","filesize":[{"value":"1.9 MB"}],"format":"application/pdf","licensetype":"license_note","mimetype":"application/pdf","url":{"label":"j97-d_5_953","url":"https://uec.repo.nii.ac.jp/record/9092/files/j97-d_5_953.pdf"},"version_id":"50a160bf-3b91-49bd-8d4a-d78fde75ba1e"}]},"item_keyword":{"attribute_name":"キーワード","attribute_value_mlt":[{"subitem_subject":"ユビキタスコンピューティング","subitem_subject_scheme":"Other"},{"subitem_subject":"プライバシー","subitem_subject_scheme":"Other"},{"subitem_subject":"匿名化","subitem_subject_scheme":"Other"},{"subitem_subject":"ubiquitous computing","subitem_subject_language":"en","subitem_subject_scheme":"Other"},{"subitem_subject":"privacy","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":"Randomized Responseを用いた柔軟な匿名データ収集","item_titles":{"attribute_name":"タイトル","attribute_value_mlt":[{"subitem_title":"Randomized Responseを用いた柔軟な匿名データ収集","subitem_title_language":"ja"},{"subitem_title":"Flexible Anonymized Data Collection with Randomized Response Scheme","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":"9092","relation_version_is_last":true,"title":["Randomized Responseを用いた柔軟な匿名データ収集"],"weko_creator_id":"13","weko_shared_id":-1},"updated":"2024-03-04T04:05:23.670139+00:00"}