Abstract
The significant growth of medical data has necessitated the development of secure health-care recommender systems to assist people with their health-being effectively. Unfortunately, there is still a considerable gap between the performance of secure recommender systems and normal versions. In this work, we develop a privacy-preserving health-care recommendation algorithm to reduce that gap. The main strength of our contribution lies in providing a highly efficient solution, while the sensitive medical data are kept confidential. Our studies show that the runtime of our protocol is 81,5% faster than the existing implementation for small bit-lengths, and even more so for large bit-lengths.
Original language | English |
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Title of host publication | Proceedings of the 15th International Joint Conference on e-Business and Telecommunications |
Editors | P. Samarati, M.S. Obaisat |
Publisher | SciTePress |
Pages | 188-199 |
Number of pages | 12 |
Volume | 1: SECRYPT |
ISBN (Print) | 978-989-758-319-3 |
DOIs | |
Publication status | Published - 2018 |
Event | ICETE 2018: The15th International Joint Conference on e-Business and Telecommunications - Porto, Portugal Duration: 26 Jul 2018 → 28 Jul 2018 Conference number: 15 |
Conference
Conference | ICETE 2018 |
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Country/Territory | Portugal |
City | Porto |
Period | 26/07/18 → 28/07/18 |
Keywords
- Recommender System
- Privacy-preserving
- Homomorphic Encryption
- Multi-party Computation
- Comparison Protocol