K. Y. Yigzaw, J. G. Bellika, Anders Andersen, G. Hartvigsen, C. Fernández-Llatas
{"title":"分布式电子病历数据的隐私保护计算研究","authors":"K. Y. Yigzaw, J. G. Bellika, Anders Andersen, G. Hartvigsen, C. Fernández-Llatas","doi":"10.1145/2541534.2541593","DOIUrl":null,"url":null,"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.","PeriodicalId":318237,"journal":{"name":"MDS '13","volume":"30 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2013-12-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"14","resultStr":"{\"title\":\"Towards privacy-preserving computing on distributed electronic health record data\",\"authors\":\"K. Y. Yigzaw, J. G. Bellika, Anders Andersen, G. Hartvigsen, C. Fernández-Llatas\",\"doi\":\"10.1145/2541534.2541593\",\"DOIUrl\":null,\"url\":null,\"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.\",\"PeriodicalId\":318237,\"journal\":{\"name\":\"MDS '13\",\"volume\":\"30 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2013-12-09\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"14\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"MDS '13\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1145/2541534.2541593\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"MDS '13","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/2541534.2541593","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Towards privacy-preserving computing on distributed electronic health record data
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.