Privacy-preserving analytics : secure logistic regression
Much data and information have been collected about us from all aspects of our life. Sometimes, we need to do analysis on this data without violating the privacy of individuals. In this project, we present a cryptographic library that can be used to do logistic regression under encrypted data. The e...
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sg-ntu-dr.10356-771262023-03-03T20:42:55Z Privacy-preserving analytics : secure logistic regression Djonatan, Prabowo Ng Wee Keong School of Computer Science and Engineering Zhu Huafei DRNTU::Engineering::Computer science and engineering Much data and information have been collected about us from all aspects of our life. Sometimes, we need to do analysis on this data without violating the privacy of individuals. In this project, we present a cryptographic library that can be used to do logistic regression under encrypted data. The encryption scheme used is a multiparty computation based on Exponential ElGamal. A special type of multiplication gate, the conditional gate, helps in the realization of the library. An implementation of the library usage on predicting the severity of heart disease based on the encrypted patient’s attributes is also presented along this project. Bachelor of Engineering (Computer Science) 2019-05-09T08:11:51Z 2019-05-09T08:11:51Z 2019 Final Year Project (FYP) http://hdl.handle.net/10356/77126 en Nanyang Technological University 35 p. application/pdf |
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Singapore Singapore |
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DRNTU::Engineering::Computer science and engineering |
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DRNTU::Engineering::Computer science and engineering Djonatan, Prabowo Privacy-preserving analytics : secure logistic regression |
| description |
Much data and information have been collected about us from all aspects of our life. Sometimes, we need to do analysis on this data without violating the privacy of individuals. In this project, we present a cryptographic library that can be used to do logistic regression under encrypted data. The encryption scheme used is a multiparty computation based on Exponential ElGamal. A special type of multiplication gate, the conditional gate, helps in the realization of the library. An implementation of the library usage on predicting the severity of heart disease based on the encrypted patient’s attributes is also presented along this project. |
| author2 |
Ng Wee Keong |
| author_facet |
Ng Wee Keong Djonatan, Prabowo |
| format |
Final Year Project |
| author |
Djonatan, Prabowo |
| author_sort |
Djonatan, Prabowo |
| title |
Privacy-preserving analytics : secure logistic regression |
| title_short |
Privacy-preserving analytics : secure logistic regression |
| title_full |
Privacy-preserving analytics : secure logistic regression |
| title_fullStr |
Privacy-preserving analytics : secure logistic regression |
| title_full_unstemmed |
Privacy-preserving analytics : secure logistic regression |
| title_sort |
privacy-preserving analytics : secure logistic regression |
| publishDate |
2019 |
| url |
http://hdl.handle.net/10356/77126 |
| _version_ |
1759857673541517312 |