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        <datestamp>2024-03-06T11:02:57Z</datestamp>
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          <dc:title>Anonymous Routing Using Minimum Capacity Clustering (Short Paper)</dc:title>
          <dc:creator>Buchin, Maike</dc:creator>
          <dc:creator>Plätz, Lukas</dc:creator>
          <dc:subject>Anonymity</dc:subject>
          <dc:subject>approximation Algorithms</dc:subject>
          <dc:subject>directed Networks</dc:subject>
          <dc:subject>minimum capacity Clustering</dc:subject>
          <dc:subject>Privacy</dc:subject>
          <dc:description>We present a framework which allows one to use an online routing service and get live updates without revealing the sensitive starting and ending points of one’s route. For that, we obfuscate the starting and ending locations in minimum capacity clusters and reveal only the route between these clusters. We compare different anonymous clustering strategies on positions in the network with efficient approximations and analyse the impact of the anonymisation on the route. We experimentally evaluate the effect of the anonymisation scheme in real-world settings.</dc:description>
          <dc:publisher>Schloss Dagstuhl – Leibniz-Zentrum für Informatik</dc:publisher>
          <dc:contributor>Maike Buchin and Lukas Plätz</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>
          <dc:type>Text</dc:type>
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          <dc:identifier>doi:10.4230/LIPIcs.GIScience.2023.18</dc:identifier>
          <dc:identifier>urn:nbn:de:0030-drops-189131</dc:identifier>
          <dc:identifier>https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.GIScience.2023.18</dc:identifier>
          <dc:language>eng</dc:language>
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