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Secure Health Monitoring in the Cloud Using Homomorphic Encryption: A Branching-Program Formulation

Secure Health Monitoring in the Cloud Using Homomorphic Encryption: A Branching-Program Formulation

Scott Ames, Muthuramakrishnan Venkitasubramaniam, Alex Page, Ovunc Kocabas, Tolga Soyata
Copyright: © 2015 |Pages: 37
ISBN13: 9781466686625|ISBN10: 1466686626|EISBN13: 9781466686632
DOI: 10.4018/978-1-4666-8662-5.ch004
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MLA

Ames, Scott, et al. "Secure Health Monitoring in the Cloud Using Homomorphic Encryption: A Branching-Program Formulation." Enabling Real-Time Mobile Cloud Computing through Emerging Technologies, edited by Tolga Soyata, IGI Global, 2015, pp. 116-152. https://doi.org/10.4018/978-1-4666-8662-5.ch004

APA

Ames, S., Venkitasubramaniam, M., Page, A., Kocabas, O., & Soyata, T. (2015). Secure Health Monitoring in the Cloud Using Homomorphic Encryption: A Branching-Program Formulation. In T. Soyata (Ed.), Enabling Real-Time Mobile Cloud Computing through Emerging Technologies (pp. 116-152). IGI Global. https://doi.org/10.4018/978-1-4666-8662-5.ch004

Chicago

Ames, Scott, et al. "Secure Health Monitoring in the Cloud Using Homomorphic Encryption: A Branching-Program Formulation." In Enabling Real-Time Mobile Cloud Computing through Emerging Technologies, edited by Tolga Soyata, 116-152. Hershey, PA: IGI Global, 2015. https://doi.org/10.4018/978-1-4666-8662-5.ch004

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Abstract

Extending cloud computing to medical software, where the hospitals rent the software from the provider sounds like a natural evolution for cloud computing. One problem with cloud computing, though, is ensuring the medical data privacy in applications such as long term health monitoring. Previously proposed solutions based on Fully Homomorphic Encryption (FHE) completely eliminate privacy concerns, but are extremely slow to be practical. Our key proposition in this paper is a new approach to applying FHE into the data that is stored in the cloud. Instead of using the existing circuit-based programming models, we propose a solution based on Branching Programs. While this restricts the type of data elements that FHE can be applied to, it achieves dramatic speed-up as compared to traditional circuit-based methods. Our claims are proven with simulations applied to real ECG data.

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