Privacy-Preserving Maximum Matching on General Graphs and its Application to Enable Privacy-Preserving Kidney Exchange

Author:

Breuer Malte1,Meyer Ulrike1,Wetzel Susanne2

Affiliation:

1. RWTH Aachen University, Aachen, Germany

2. Stevens Institute of Technology, Hoboken, NJ, USA

Funder

National Science Foundation

Deutsche Forschungsgemeinschaft

Publisher

ACM

Cited by 7 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. A neural algorithm for computing bipartite matchings;Proceedings of the National Academy of Sciences;2024-09-03

2. Prioritization and exchange chains in privacy-preserving kidney exchange;Journal of Computer Security;2024-08-26

3. Efficient Privacy-Preserving Approximation of the Kidney Exchange Problem;Proceedings of the 19th ACM Asia Conference on Computer and Communications Security;2024-07

4. Privacy-Preserving Fully Online Matching with Deadlines;Proceedings of the Thirteenth ACM Conference on Data and Application Security and Privacy;2023-04-24

5. Secure Maximum Weight Matching Approximation on General Graphs;Proceedings of the 21st Workshop on Privacy in the Electronic Society;2022-11-07

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