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Towards privacy-preserving computing on distributed electronic health record data
| Content Provider | ACM Digital Library |
|---|---|
| Author | Bellika, Johan Gustav Yigzaw, Kassaye Yitbarek Hartvigsen, Gunnar Andersen, Anders Fernandez-Llatas, Carlos |
| Abstract | The paper reports on work in progress towards construction of a peer-to-peer framework for privacy preserving computing on distributed electronic health data. The framework supports three different types of federated queries. For privacy-preserving computing, we proposed distributed secure multi-party computation (SMC), where each peer is only involved in secure computations with some of the peers. We hypothesize distributed SMC could enable to achieve more efficient and scalable computing solutions. The architecture of the framework is also described. |
| Starting Page | 1 |
| Ending Page | 6 |
| Page Count | 6 |
| File Format | |
| ISBN | 9781450325486 |
| DOI | 10.1145/2541534.2541593 |
| Language | English |
| Publisher | Association for Computing Machinery (ACM) |
| Publisher Date | 2013-12-09 |
| Publisher Place | New York |
| Access Restriction | Subscribed |
| Subject Keyword | Secure multi-party computation Peer-to-peer system Statistical computation Privacy-preserving Electronic health record Distributed data network Federated query |
| Content Type | Text |
| Resource Type | Article |
