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University","subitem_text_language":"en"},{"subitem_text_value":"Graduate School of Meiji University","subitem_text_language":"en"},{"subitem_text_value":"Graduate School of Meiji University","subitem_text_language":"en"},{"subitem_text_value":"Meiji University","subitem_text_language":"en"},{"subitem_text_value":"Meiji University","subitem_text_language":"en"},{"subitem_text_value":"Meiji University","subitem_text_language":"en"}]},"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/187330/files/IPSJCSS2017155.pdf","label":"IPSJCSS2017155.pdf"},"date":[{"dateType":"Available","dateValue":"2019-10-16"}],"format":"application/pdf","billing":["billing_file"],"filename":"IPSJCSS2017155.pdf","filesize":[{"value":"511.4 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Fingerprintingと呼ばれる手法がある．既存研究においてさまざまな特徴点が提案されたが，特徴点の組み合わせと識別精度の相関関係については議論されてこなかった．本論文では，我々の研究グループが運営するWebサイトで採取した9,457サンプルを用いて特徴点の組み合わせにおける精度を算出し，識別精度が最良となる組み合わせをOSごとに求めた．その結果先行研究と比較し，Windowsでは1.006%，Macでは3.894%，iOSでは7.456%，Androidでは3.840%の精度の向上を実現した．","subitem_description_type":"Other"}]},"item_18_biblio_info_10":{"attribute_name":"書誌情報","attribute_value_mlt":[{"bibliographic_titles":[{"bibliographic_title":"コンピュータセキュリティシンポジウム2017論文集"}],"bibliographicIssueDates":{"bibliographicIssueDate":"2017-10-16","bibliographicIssueDateType":"Issued"},"bibliographicIssueNumber":"2","bibliographicVolumeNumber":"2017"}]},"relation_version_is_last":true,"weko_creator_id":"11"},"id":187330,"links":{}}