{"_buckets": {"deposit": "aa73897b-6d75-4ed5-94c9-40ce857517aa"}, "_deposit": {"created_by": 13, "id": "9093", "owners": [13], "pid": {"revision_id": 0, "type": "depid", "value": "9093"}, "status": "published"}, "_oai": {"id": "oai:uec.repo.nii.ac.jp:00009093", "sets": ["6"]}, "author_link": ["24288", "24290", "24293", "24295"], "control_number": "9093", "item_10001_biblio_info_7": {"attribute_name": "書誌情報", "attribute_value_mlt": [{"bibliographicIssueDates": {"bibliographicIssueDate": "2014-04-01", "bibliographicIssueDateType": "Issued"}, "bibliographicIssueNumber": "4", "bibliographicPageEnd": "806", "bibliographicPageStart": "793", "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": "ユビキタスコンピューティング環境において多くのユーザからセンシングしたデータを収集し，その分布を把握することによって，国の政策や企業における意思決定に役立てることができる．しかし，これらのデータには個人を特定できる情報が含まれることがあり，ユーザのプライバシー情報が漏洩するリスクがある．このような問題に対応し，全てのユーザが必ず正しくない情報を提供することで，プライバシーを保護しつつ，サーバ側で真のデータ分布を推測するNegative Surveyという手法が提案されている．従来のNegative Surveyでは多数のユーザ情報を収集しなければ分布を高精度に推測できないという欠点があった．近年，少ないユーザ数から真の分布を推測することができる手法が複数提案されているが，いずれもプライバシー保護レベルが低いという課題がある．本研究では，プライバシー保護レベルを一定レベルに保ち，従来手法よりも真の分布に近い情報を得られる手法を提案する．近年提案されている手法と比較して平均2乗誤差を約1/2から1/30程度にまで削減できることを数学的解析及びシミュレーションによって示す．", "subitem_description_type": "Abstract"}, {"subitem_description": "Ubiquitous computing can collect sensing data of users. These data can be used for national policy or decision-making of companies. However, sensing users may violate their privacy. Negative surveys collect incorrect data of each user and can assume true data distributions of users. Traditional negative survey needs a lot of samples for precise estimation. These days several types of negative surveys, which can estimate data distributions with a high degree of accuracy, are proposed. However, a privacy level of these methods is relatively low. In this paper, we propose a new negative survey which can estimate data distributions with more precision and protect privacy more strictly. By mathematical analysis and simulations, we prove tha our proposed method can reduce MSE by between approximately 1/2 and 1/30.", "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"}], "nameIdentifiers": [{"nameIdentifier": "24288", "nameIdentifierScheme": "WEKO"}]}, {"creatorNames": [{"creatorName": "大須賀, 昭彦", "creatorNameLang": "ja"}, {"creatorName": "オオスガ, アキヒコ", "creatorNameLang": "ja-Kana"}], "nameIdentifiers": [{"nameIdentifier": "24290", "nameIdentifierScheme": "WEKO"}]}, {"creatorNames": [{"creatorName": "SEI, Yuichi", "creatorNameLang": "en"}], "nameIdentifiers": [{"nameIdentifier": "24293", "nameIdentifierScheme": "WEKO"}]}, {"creatorNames": [{"creatorName": "OHSUGA, Akihiko", "creatorNameLang": "en"}], "nameIdentifiers": [{"nameIdentifier": "24295", "nameIdentifierScheme": "WEKO"}]}]}, "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", "download_preview_message": "", "file_order": 0, "filename": "j97-d_4_793.pdf", "filesize": [{"value": "1.1 MB"}], "format": "application/pdf", "future_date_message": "", "is_thumbnail": false, "licensetype": "license_free", "mimetype": "application/pdf", "size": 1100000.0, "url": {"label": "j97-d_4_793", "url": "https://uec.repo.nii.ac.jp/record/9093/files/j97-d_4_793.pdf"}, "version_id": "98febcee-6723-4264-b131-aa9b04fcbb6c"}]}, "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": "ユビキタスコンピューティングにおけるl-エントロピーを満たす匿名データ収集", "item_titles": {"attribute_name": "タイトル", "attribute_value_mlt": [{"subitem_title": "ユビキタスコンピューティングにおけるl-エントロピーを満たす匿名データ収集", "subitem_title_language": "ja"}, {"subitem_title": "Anonymized Data Collection Satisfying l-Entropy in Ubiquitous Computing", "subitem_title_language": "en"}]}, "item_type_id": "10001", "owner": "13", "path": ["6"], "permalink_uri": "https://uec.repo.nii.ac.jp/records/9093", "pubdate": {"attribute_name": "PubDate", "attribute_value": "2019-04-09"}, "publish_date": "2019-04-09", "publish_status": "0", "recid": "9093", "relation": {}, "relation_version_is_last": true, "title": ["ユビキタスコンピューティングにおけるl-エントロピーを満たす匿名データ収集"], "weko_shared_id": -1}