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        <identifier>oai:ipsj.ixsq.nii.ac.jp:00218876</identifier>
        <datestamp>2025-01-19T15:00:07Z</datestamp>
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          <dc:title>ブラウザフィンガープリンティングにおけるプライバシーを考慮したWebサイト利用者の識別・追跡</dc:title>
          <dc:title xml:lang="en">Identification and tracking of website users in consideration of privacy in browser fingerprinting</dc:title>
          <jpcoar:creator>
            <jpcoar:creatorName>塚崎, 崇至</jpcoar:creatorName>
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          <jpcoar:creator>
            <jpcoar:creatorName>布田, 裕一</jpcoar:creatorName>
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          <jpcoar:creator>
            <jpcoar:creatorName>鈴木, 智道</jpcoar:creatorName>
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          <jpcoar:creator>
            <jpcoar:creatorName>岡崎, 裕之</jpcoar:creatorName>
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          <jpcoar:creator>
            <jpcoar:creatorName xml:lang="en">Takashi, Tsukazaki</jpcoar:creatorName>
          </jpcoar:creator>
          <jpcoar:creator>
            <jpcoar:creatorName xml:lang="en">Yuichi, Futa</jpcoar:creatorName>
          </jpcoar:creator>
          <jpcoar:creator>
            <jpcoar:creatorName xml:lang="en">Tomomichi, Suzuki</jpcoar:creatorName>
          </jpcoar:creator>
          <jpcoar:creator>
            <jpcoar:creatorName xml:lang="en">Hiroyuki, Okazaki</jpcoar:creatorName>
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          <jpcoar:subject subjectScheme="Other">ICSS</jpcoar:subject>
          <datacite:description descriptionType="Other">Web ユーザーの識別手段としてブラウザフィンガープリンティングがある．ブラウザフィンガープリンティングでは，Web サイトにアクセスしてきたユーザーから特徴点と呼ばれる端末情報を採取し，ユーザーを識別する．我々の前回の研究では，91 個の特徴点を用いたフィンガープリンティングを実施した．本稿では，前回の研究よりも少ない 21 個の特徴点を用いたフィンガープリンティングを提案する．また，識別・追跡精度の算出では，Web ブラウザの特徴点を完全一致による比較，HTTP リクエストヘッダと通信パケットの特徴点を類似度による比較として評価を行った．識別・追跡精度の評価より，識別精度は約 57.832% となり，追跡精度は 100% となった．前回の研究よりも識別精度，追跡精度はそれぞれ向上した．</datacite:description>
          <datacite:description descriptionType="Other">Browser fingerprinting is to identify website users by collecting information about device. In our previous research, we proposed a browser fingerprinting method which uses much information about device. In this report, we propose a browser fingerprinting method which uses a little information about device. In the calculation of identification and tracking accuracy, information from web browser is evaluated as a comparison by exact match, and information from HTTP request header and network packet is evaluated as a comparison by similarity. As a result of evaluation of our method, identification accuracy was about 57.832% and tracking accuracy was 100%. Identification accuracy and tracking accuracy improved than our previous research.</datacite:description>
          <dc:publisher xml:lang="ja">情報処理学会</dc:publisher>
          <datacite:date dateType="Issued">2022-07-12</datacite:date>
          <dc:language>jpn</dc:language>
          <dc:type rdf:resource="http://purl.org/coar/resource_type/c_18gh">technical report</dc:type>
          <jpcoar:identifier identifierType="URI">https://ipsj.ixsq.nii.ac.jp/records/218876</jpcoar:identifier>
          <jpcoar:sourceIdentifier identifierType="ISSN">2188-8671</jpcoar:sourceIdentifier>
          <jpcoar:sourceIdentifier identifierType="NCID">AA12628305</jpcoar:sourceIdentifier>
          <jpcoar:sourceTitle>研究報告セキュリティ心理学とトラスト（SPT）</jpcoar:sourceTitle>
          <jpcoar:volume>2022-SPT-48</jpcoar:volume>
          <jpcoar:issue>32</jpcoar:issue>
          <jpcoar:pageStart>1</jpcoar:pageStart>
          <jpcoar:pageEnd>7</jpcoar:pageEnd>
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