Sharing Privacy Protected and Statistically Sound Clinical Research Data Using Outsourced Data Storage

Joint Authors

Noh, Geontae
Jeong, Ik Rae
Chun, Ji Young

Source

Journal of Applied Mathematics

Issue

Vol. 2014, Issue 2014 (31 Dec. 2014), pp.1-12, 12 p.

Publisher

Hindawi Publishing Corporation

Publication Date

2014-05-18

Country of Publication

Egypt

No. of Pages

12

Main Subjects

Mathematics

Abstract EN

It is critical to scientific progress to share clinical research data stored in outsourced generally available cloud computing services.

Researchers are able to obtain valuable information that they would not otherwise be able to access; however, privacy concerns arise when sharing clinical data in these outsourced publicly available data storage services.

HIPAA requires researchers to deidentify private information when disclosing clinical data for research purposes and describes two available methods for doing so.

Unfortunately, both techniques degrade statistical accuracy.

Therefore, the need to protect privacy presents a significant problem for data sharing between hospitals and researchers.

In this paper, we propose a controlled secure aggregation protocol to secure both privacy and accuracy when researchers outsource their clinical research data for sharing.

Since clinical data must remain private beyond a patient’s lifetime, we take advantage of lattice-based homomorphic encryption to guarantee long-term security against quantum computing attacks.

Using lattice-based homomorphic encryption, we design an aggregation protocol that aggregates outsourced ciphertexts under distinct public keys.

It enables researchers to get aggregated results from outsourced ciphertexts of distinct researchers.

To the best of our knowledge, our protocol is the first aggregation protocol which can aggregate ciphertexts which are encrypted with distinct public keys.

American Psychological Association (APA)

Noh, Geontae& Chun, Ji Young& Jeong, Ik Rae. 2014. Sharing Privacy Protected and Statistically Sound Clinical Research Data Using Outsourced Data Storage. Journal of Applied Mathematics،Vol. 2014, no. 2014, pp.1-12.
https://search.emarefa.net/detail/BIM-467568

Modern Language Association (MLA)

Noh, Geontae…[et al.]. Sharing Privacy Protected and Statistically Sound Clinical Research Data Using Outsourced Data Storage. Journal of Applied Mathematics No. 2014 (2014), pp.1-12.
https://search.emarefa.net/detail/BIM-467568

American Medical Association (AMA)

Noh, Geontae& Chun, Ji Young& Jeong, Ik Rae. Sharing Privacy Protected and Statistically Sound Clinical Research Data Using Outsourced Data Storage. Journal of Applied Mathematics. 2014. Vol. 2014, no. 2014, pp.1-12.
https://search.emarefa.net/detail/BIM-467568

Data Type

Journal Articles

Language

English

Notes

Includes bibliographical references

Record ID

BIM-467568