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Authors: Danilo Verhaert ; Majid Nateghizad and Zekeriya Erkin

Affiliation: Cyber Security Group, Department of Intelligent Systems, Delft University of Technology and The Netherlands

ISBN: 978-989-758-319-3

Keyword(s): Recommender System, Privacy-preserving, Homomorphic Encryption, Multi-party Computation, Comparison Protocol.

Related Ontology Subjects/Areas/Topics: Applied Cryptography ; Cryptographic Techniques and Key Management ; Data and Application Security and Privacy ; Data Engineering ; Databases and Data Security ; Information and Systems Security ; Privacy ; Privacy Enhancing Technologies

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.

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Paper citation in several formats:
Verhaert, D.; Nateghizad, M. and Erkin, Z. (2018). An Efficient Privacy-preserving Recommender System for e-Healthcare Systems.In Proceedings of the 15th International Joint Conference on e-Business and Telecommunications - Volume 1: SECRYPT, ISBN 978-989-758-319-3, pages 188-199. DOI: 10.5220/0006858503540365

@conference{secrypt18,
author={Danilo Verhaert. and Majid Nateghizad. and Zekeriya Erkin.},
title={An Efficient Privacy-preserving Recommender System for e-Healthcare Systems},
booktitle={Proceedings of the 15th International Joint Conference on e-Business and Telecommunications - Volume 1: SECRYPT,},
year={2018},
pages={188-199},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0006858503540365},
isbn={978-989-758-319-3},
}

TY - CONF

JO - Proceedings of the 15th International Joint Conference on e-Business and Telecommunications - Volume 1: SECRYPT,
TI - An Efficient Privacy-preserving Recommender System for e-Healthcare Systems
SN - 978-989-758-319-3
AU - Verhaert, D.
AU - Nateghizad, M.
AU - Erkin, Z.
PY - 2018
SP - 188
EP - 199
DO - 10.5220/0006858503540365

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