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        <identifier>oai:ipsj.ixsq.nii.ac.jp:00145065</identifier>
        <datestamp>2025-01-20T06:25:14Z</datestamp>
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        <jpcoar:jpcoar xmlns:datacite="https://schema.datacite.org/meta/kernel-4/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:dcndl="http://ndl.go.jp/dcndl/terms/" xmlns:dcterms="http://purl.org/dc/terms/" xmlns:jpcoar="https://github.com/JPCOAR/schema/blob/master/1.0/" xmlns:oaire="http://namespace.openaire.eu/schema/oaire/" xmlns:rdf="http://www.w3.org/1999/02/22-rdf-syntax-ns#" xmlns:rioxxterms="http://www.rioxx.net/schema/v2.0/rioxxterms/" xmlns:xs="http://www.w3.org/2001/XMLSchema" xmlns="https://github.com/JPCOAR/schema/blob/master/1.0/" xsi:schemaLocation="https://github.com/JPCOAR/schema/blob/master/1.0/jpcoar_scm.xsd">
          <dc:title>大規模集計データへの差分プライバシの適用</dc:title>
          <dc:title xml:lang="en">On Publishing Large Tabular Data with Differential Privacy</dc:title>
          <jpcoar:creator>
            <jpcoar:creatorName>寺田, 雅之</jpcoar:creatorName>
          </jpcoar:creator>
          <jpcoar:creator>
            <jpcoar:creatorName>鈴木, 亮平</jpcoar:creatorName>
          </jpcoar:creator>
          <jpcoar:creator>
            <jpcoar:creatorName>山口, 高康</jpcoar:creatorName>
          </jpcoar:creator>
          <jpcoar:creator>
            <jpcoar:creatorName>本郷, 節之</jpcoar:creatorName>
          </jpcoar:creator>
          <jpcoar:creator>
            <jpcoar:creatorName xml:lang="en">Masayuki, Terada</jpcoar:creatorName>
          </jpcoar:creator>
          <jpcoar:creator>
            <jpcoar:creatorName xml:lang="en">Ryohei, Suzuki</jpcoar:creatorName>
          </jpcoar:creator>
          <jpcoar:creator>
            <jpcoar:creatorName xml:lang="en">Takayasu, Yamaguchi</jpcoar:creatorName>
          </jpcoar:creator>
          <jpcoar:creator>
            <jpcoar:creatorName xml:lang="en">Sadayuki, Hongo</jpcoar:creatorName>
          </jpcoar:creator>
          <jpcoar:subject subjectScheme="Other">[特集：社会に浸透していくコンピュータセキュリティ技術（推薦論文, 特選論文）] プライバシ保護，差分プライバシ，ウェーブレット変換，非負制約（論文賞受賞）</jpcoar:subject>
          <datacite:description descriptionType="Other">データの有効な活用による社会・産業の発展への期待が高まる中，プライバシを保護したうえでデータを利用するための技術が注目を集めている．そのなかで，Dworkらによる差分プライバシは，その高い安全性から大きな期待が寄せられているが，特に大規模データへの適用においてデータの有用性や処理効率などの観点から実用上の課題を持つ．本稿では，地理空間データなどの大規模な集計データに差分プライバシを適用するうえでの課題を示すとともに，これを解決する手法について安全性証明と実データに基づく評価を与える．本手法は，集計データの非負制約に着目し，その逸脱をWavelet空間において補正する過程を導入することにより有用性と処理効率の向上を実現するとともに，局所性保存写像（locality preserving mapping）の一種であるMorton順序写像を用いることにより，地理空間データなどの多次元集計データへの適用時の精度劣化を抑制することを特徴とする．</datacite:description>
          <datacite:description descriptionType="Other">Big data become widely expected to enhance the quality and efficiency of our daily life, and methods to prevent privacy information included in the data from being disclosed by data utilization become attracting wide attention therewith. Differential privacy is a promising paradigms to achieve proven privacy, but previous methods to assure the differential privacy have several drawbacks on data utility and scalability in practice, in particular when applied to publishing large and sparse tabular data such as geospatial data. This paper proposes a novel differentially private method that simultaneously solves these problems, and demonstrates its evaluation results. The proposed method introduces a process to correct for the non-negative restriction of the output data by modifying the wavelet coefficients of the perturbed data, and this correction process enables the proposed method to efficiently process large sparse data in terms of scalability and accuracy. In addition, the proposed method effectively suppresses the amount of noise required to process multi-dimensional data by reducing its dimensionality using a locality-preserving mapping method called Morton order mapping.</datacite:description>
          <datacite:date dateType="Issued">2015-09-15</datacite:date>
          <dc:language>jpn</dc:language>
          <dc:type rdf:resource="http://purl.org/coar/resource_type/c_6501">journal article</dc:type>
          <jpcoar:identifier identifierType="URI">https://ipsj.ixsq.nii.ac.jp/records/145065</jpcoar:identifier>
          <jpcoar:sourceIdentifier identifierType="ISSN">1882-7764</jpcoar:sourceIdentifier>
          <jpcoar:sourceIdentifier identifierType="NCID">AN00116647</jpcoar:sourceIdentifier>
          <jpcoar:sourceTitle>情報処理学会論文誌</jpcoar:sourceTitle>
          <jpcoar:volume>56</jpcoar:volume>
          <jpcoar:issue>9</jpcoar:issue>
          <jpcoar:pageStart>1801</jpcoar:pageStart>
          <jpcoar:pageEnd>1816</jpcoar:pageEnd>
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            <datacite:date dateType="Available">2017-09-15</datacite:date>
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