{"title":"有效地利用云来安全地求解线性回归和其他矩阵运算","authors":"Youwen Zhu, Zhikuan Wang, Cheng Qian, Jian Wang","doi":"10.1109/IWQoS.2016.7590402","DOIUrl":null,"url":null,"abstract":"In this paper, we propose a new efficient solution for securely outsourcing linear regression to a public cloud with robust answer verification. Additionally, we show our construction can be utilized to efficiently and securely outsource other large-scale matrix operations, such as determinant computation.","PeriodicalId":304978,"journal":{"name":"2016 IEEE/ACM 24th International Symposium on Quality of Service (IWQoS)","volume":"29 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2016-06-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":"{\"title\":\"On efficiently harnessing cloud to securely solve linear regression and other matrix operations\",\"authors\":\"Youwen Zhu, Zhikuan Wang, Cheng Qian, Jian Wang\",\"doi\":\"10.1109/IWQoS.2016.7590402\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In this paper, we propose a new efficient solution for securely outsourcing linear regression to a public cloud with robust answer verification. Additionally, we show our construction can be utilized to efficiently and securely outsource other large-scale matrix operations, such as determinant computation.\",\"PeriodicalId\":304978,\"journal\":{\"name\":\"2016 IEEE/ACM 24th International Symposium on Quality of Service (IWQoS)\",\"volume\":\"29 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2016-06-20\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"3\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2016 IEEE/ACM 24th International Symposium on Quality of Service (IWQoS)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/IWQoS.2016.7590402\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2016 IEEE/ACM 24th International Symposium on Quality of Service (IWQoS)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/IWQoS.2016.7590402","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
On efficiently harnessing cloud to securely solve linear regression and other matrix operations
In this paper, we propose a new efficient solution for securely outsourcing linear regression to a public cloud with robust answer verification. Additionally, we show our construction can be utilized to efficiently and securely outsource other large-scale matrix operations, such as determinant computation.