{"created":"2025-01-18T22:50:26.222034+00:00","updated":"2025-01-22T23:20:27.326505+00:00","metadata":{"_oai":{"id":"oai:ipsj.ixsq.nii.ac.jp:00017434","sets":["934:1022:1029:1032"]},"path":["1032"],"owner":"1","recid":"17434","title":["A High Collusion-Resistant Approach to Distributed Privacy-preserving Data Mining"],"pubdate":{"attribute_name":"公開日","attribute_value":"2007-06-15"},"_buckets":{"deposit":"c90ef58d-c828-41c8-b41e-f05e82ce7244"},"_deposit":{"id":"17434","pid":{"type":"depid","value":"17434","revision_id":0},"owners":[1],"status":"published","created_by":1},"item_title":"A High Collusion-Resistant Approach to Distributed Privacy-preserving Data Mining","author_link":["0","0"],"item_titles":{"attribute_name":"タイトル","attribute_value_mlt":[{"subitem_title":"A High Collusion-Resistant Approach to Distributed Privacy-preserving Data Mining"},{"subitem_title":"A High Collusion-Resistant Approach to Distributed Privacy-preserving Data Mining","subitem_title_language":"en"}]},"item_keyword":{"attribute_name":"キーワード","attribute_value_mlt":[{"subitem_subject":"研究論文","subitem_subject_scheme":"Other"}]},"item_type_id":"3","publish_date":"2007-06-15","item_3_text_3":{"attribute_name":"著者所属","attribute_value_mlt":[{"subitem_text_value":"Faculty of Software and Information Science  Iwate Prefectural University   Presently with Hitachi East Japan Solutions"},{"subitem_text_value":"Faculty of Software and Information Science  Iwate Prefectural University"},{"subitem_text_value":"Faculty of Software and Information Science  Iwate Prefectural University"},{"subitem_text_value":"Faculty of Software and Information Science  Iwate Prefectural University"}]},"item_3_text_4":{"attribute_name":"著者所属(英)","attribute_value_mlt":[{"subitem_text_value":"Faculty of Software and Information Science, Iwate Prefectural University , Presently with Hitachi East Japan Solutions","subitem_text_language":"en"},{"subitem_text_value":"Faculty of Software and Information Science, Iwate Prefectural University","subitem_text_language":"en"},{"subitem_text_value":"Faculty of Software and Information Science, Iwate Prefectural University","subitem_text_language":"en"},{"subitem_text_value":"Faculty of Software and Information Science, Iwate Prefectural University","subitem_text_language":"en"}]},"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/17434/files/IPSJ-TOD4811012.pdf"},"date":[{"dateType":"Available","dateValue":"2009-06-15"}],"format":"application/pdf","billing":["billing_file"],"filename":"IPSJ-TOD4811012.pdf","filesize":[{"value":"1.1 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":"13"},{"tax":["include_tax"],"price":"0","billingrole":"39"},{"tax":["include_tax"],"price":"0","billingrole":"44"}],"accessrole":"open_date","version_id":"e7167ecb-8420-4b47-88fa-2cc06647e338","displaytype":"detail","licensetype":"license_note","license_note":"Copyright (c) 2007 by the Information Processing Society of Japan"}]},"item_3_creator_5":{"attribute_name":"著者名","attribute_type":"creator","attribute_value_mlt":[{"creatorNames":[{"creatorName":"Shintaro, Urabe"},{"creatorName":"Jiahong, Wang"},{"creatorName":"Eiichiro, Kodama"},{"creatorName":"Toyoo, Takata"}],"nameIdentifiers":[{}]}]},"item_3_creator_6":{"attribute_name":"著者名(英)","attribute_type":"creator","attribute_value_mlt":[{"creatorNames":[{"creatorName":"Shintaro, Urabe","creatorNameLang":"en"},{"creatorName":"Jiahong, Wang","creatorNameLang":"en"},{"creatorName":"Eiichiro, Kodama","creatorNameLang":"en"},{"creatorName":"Toyoo, Takata","creatorNameLang":"en"}],"nameIdentifiers":[{}]}]},"item_3_source_id_9":{"attribute_name":"書誌レコードID","attribute_value_mlt":[{"subitem_source_identifier":"AA11464847","subitem_source_identifier_type":"NCID"}]},"item_resource_type":{"attribute_name":"資源タイプ","attribute_value_mlt":[{"resourceuri":"http://purl.org/coar/resource_type/c_6501","resourcetype":"journal article"}]},"item_3_source_id_11":{"attribute_name":"ISSN","attribute_value_mlt":[{"subitem_source_identifier":"1882-7799","subitem_source_identifier_type":"ISSN"}]},"item_3_description_7":{"attribute_name":"論文抄録","attribute_value_mlt":[{"subitem_description":"Data mining across different companies  organizations  online shops  or the likes  called sites  is necessary so as to discover valuable shared patterns  associations  trends  or dependencies in their shared data. Privacy  however  is a concern. In many situations it is required that data mining should be conducted without any privacy being violated. In response to this requirement  this paper proposes an effective distributed privacy-preserving data mining approach called CRDM (Collusion-Resistant Data Mining). CRDM is characterized by its ability to resist the collusion. Unless all sites but the victim collude  privacy of a site cannot be violated. Considering that for such applications that need not so high a level of security  excess security assurance would incur extra costs in communication  an extension scheme is also presented so that communication cost can be restrained while still maintaining a user-specified level of security. Results of both analytical and experimental performance study demonstrate the effectiveness of CRDM.","subitem_description_type":"Other"}]},"item_3_description_8":{"attribute_name":"論文抄録(英)","attribute_value_mlt":[{"subitem_description":"Data mining across different companies, organizations, online shops, or the likes, called sites, is necessary so as to discover valuable shared patterns, associations, trends, or dependencies in their shared data. Privacy, however, is a concern. In many situations it is required that data mining should be conducted without any privacy being violated. In response to this requirement, this paper proposes an effective distributed privacy-preserving data mining approach called CRDM (Collusion-Resistant Data Mining). CRDM is characterized by its ability to resist the collusion. Unless all sites but the victim collude, privacy of a site cannot be violated. Considering that for such applications that need not so high a level of security, excess security assurance would incur extra costs in communication, an extension scheme is also presented so that communication cost can be restrained while still maintaining a user-specified level of security. Results of both analytical and experimental performance study demonstrate the effectiveness of CRDM.","subitem_description_type":"Other"}]},"item_3_biblio_info_10":{"attribute_name":"書誌情報","attribute_value_mlt":[{"bibliographicPageEnd":"117","bibliographic_titles":[{"bibliographic_title":"情報処理学会論文誌データベース（TOD）"}],"bibliographicPageStart":"104","bibliographicIssueDates":{"bibliographicIssueDate":"2007-06-15","bibliographicIssueDateType":"Issued"},"bibliographicIssueNumber":"SIG11(TOD34)","bibliographicVolumeNumber":"48"}]},"relation_version_is_last":true,"weko_creator_id":"1"},"id":17434,"links":{}}