An Efficient Privacy-preserving Recommender System for e-Healthcare systems

Danilo Verhaert, Majid Nateghizad, Zekeriya Erkin

Research output: Chapter in Book/Conference proceedings/Edited volumeConference contributionScientificpeer-review

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 languageEnglish
Title of host publicationProceedings of the 15th International Joint Conference on e-Business and Telecommunications
EditorsP. Samarati, M.S. Obaisat
PublisherSciTePress
Pages188-199
Number of pages12
Volume1: SECRYPT
ISBN (Print)978-989-758-319-3
DOIs
Publication statusPublished - 2018
EventICETE 2018: The15th International Joint Conference on e-Business and Telecommunications - Porto, Portugal
Duration: 26 Jul 201828 Jul 2018
Conference number: 15

Conference

ConferenceICETE 2018
CountryPortugal
CityPorto
Period26/07/1828/07/18

Keywords

  • Recommender System
  • Privacy-preserving
  • Homomorphic Encryption
  • Multi-party Computation
  • Comparison Protocol

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