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        <identifier>oai:drops-oai.dagstuhl.de:18907</identifier>
        <datestamp>2024-03-06T11:02:56Z</datestamp>
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          <dc:title>Confidential, Decentralized Location-Based Data Services (Short Paper)</dc:title>
          <dc:creator>Adams, Benjamin</dc:creator>
          <dc:subject>spatial data</dc:subject>
          <dc:subject>privacy</dc:subject>
          <dc:subject>smart contract</dc:subject>
          <dc:subject>differential privacy</dc:subject>
          <dc:description>There are many privacy risks when location data is collected and aggregated. We introduce the notion of using confidential smart contracts for building location-based decentralized applications that are privacy preserving. We describe a spatial library for smart contracts that run on Secret Network, a blockchain network that runs smart contracts in secure enclaves running in trusted execution environments. The library supports not only basic geometric operations but also cloaking and differential privacy mechanisms applied to spatial data stored in the contract.</dc:description>
          <dc:publisher>Schloss Dagstuhl – Leibniz-Zentrum für Informatik</dc:publisher>
          <dc:contributor>Benjamin Adams</dc:contributor>
          <dc:date>2023</dc:date>
          <dc:relation>Is Part Of LIPIcs, Volume 277, 12th International Conference on Geographic Information Science (GIScience 2023)</dc:relation>
          <dc:type>InProceedings</dc:type>
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          <dc:identifier>doi:10.4230/LIPIcs.GIScience.2023.12</dc:identifier>
          <dc:identifier>urn:nbn:de:0030-drops-189078</dc:identifier>
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