IRMA-International.org: Creator of Knowledge
Information Resources Management Association
Advancing the Concepts & Practices of Information Resources Management in Modern Organizations

Towards Privacy-Preserving Medical Cloud Computing Using Homomorphic Encryption

Towards Privacy-Preserving Medical Cloud Computing Using Homomorphic Encryption
View Sample PDF
Author(s): Ovunc Kocabas (University of Rochester, USA)and Tolga Soyata (University of Rochester, USA)
Copyright: 2015
Pages: 34
Source title: Enabling Real-Time Mobile Cloud Computing through Emerging Technologies
Source Author(s)/Editor(s): Tolga Soyata (University of Rochester, USA)
DOI: 10.4018/978-1-4666-8662-5.ch007

Purchase

View Towards Privacy-Preserving Medical Cloud Computing Using Homomorphic Encryption on the publisher's website for pricing and purchasing information.

Abstract

Personal health monitoring tools, such as commercially available wireless ECG patches, can significantly reduce healthcare costs by allowing patient monitoring outside the healthcare organizations. These tools transmit the acquired medical data into the cloud, which could provide an invaluable diagnosis tool for healthcare professionals. Despite the potential of such systems to revolutionize the medical field, the adoption of medical cloud computing in general has been slow due to the strict privacy regulations on patient health information. We present a novel medical cloud computing approach that eliminates privacy concerns associated with the cloud provider. Our approach capitalizes on Fully Homomorphic Encryption (FHE), which enables computations on private health information without actually observing the underlying data. For a feasibility study, we present a working implementation of a long-term cardiac health monitoring application using a well-established open source FHE library.

Related Content

Dina Darwish. © 2024. 43 pages.
Kassim Kalinaki, Musau Abdullatif, Sempala Abdul-Karim Nasser, Ronald Nsubuga, Julius Kugonza. © 2024. 23 pages.
Yogita Yashveer Raghav, Ramesh Kait. © 2024. 17 pages.
Renuka Devi Saravanan, Shyamala Loganathan, Saraswathi Shunmuganathan. © 2024. 21 pages.
Veera Talukdar, Ardhariksa Zukhruf Kurniullah, Palak Keshwani, Huma Khan, Sabyasachi Pramanik, Ankur Gupta, Digvijay Pandey. © 2024. 30 pages.
Dharmesh Dhabliya, Sukhvinder Singh Dari, Nitin N. Sakhare, Anish Kumar Dhablia, Digvijay Pandey, Balakumar Muniandi, A. Shaji George, A. Shahul Hameed, Pankaj Dadheech. © 2024. 9 pages.
Avtar Singh, Shobhana Kashyap. © 2024. 11 pages.
Body Bottom