Secure Maximum Weight Matching Approximation on General Graphs
Authors: 
Andreas Brüggemann, Malte Breuer, Andreas Klinger, Thomas Schneider, and Ulrike MeyerAuthors Info & Claims
Andreas Brüggemann, Malte Breuer, Andreas Klinger, Thomas Schneider, and Ulrike MeyerAuthors Info & ClaimsNovember 2022
Pages 83 - 87
Abstract
Privacy-preserving protocols for matchings on general graphs can be used for applications such as online dating, bartering, or kidney donor exchange. In addition, they can act as a building block for more complex protocols. While privacy-preserving protocols for matchings on bipartite graphs are a well-researched topic, the case of general graphs has experienced significantly less attention so far. We address this gap by providing the first privacy-preserving protocol for maximum weight matching on general graphs. To maximize the scalability of our approach, we compute an 1/2-approximation instead of an exact solution. For N nodes, our protocol requires O(N log N) rounds, O(N^3) communication, and runs in only 12.5 minutes for N=400.
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Index Terms
- Secure Maximum Weight Matching Approximation on General Graphs
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Publication History
Published: 07 November 2022
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- Deutsche Forschungsgemeinschaft
- European Research Council
- German Federal Ministry of Education and Research and the Hessen State Ministry for Higher Education, Research and the Arts
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CCS '22
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CCS '22: 2022 ACM SIGSAC Conference on Computer and Communications Security
November 7, 2022
CA, Los Angeles, USA
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Overall Acceptance Rate 106 of 355 submissions, 30%
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