ECMO: An Efficient and Confidential Outsourcing Protocol for Medical Data

Cloud computing has significantly advanced medical data storage capabilities, enabling healthcare institutions to outsource data management. However, this shift introduces critical security and privacy risks, as sensitive patient information is stored on untrusted third-party servers. Existing cryptographic solutions, such as searchable encryption, offer some security guarantees but struggle with challenges like leakage-based attacks, high computational overhead, and limited scalability. To address these limitations in medical data outsourcing, we present ECMO, a novel protocol that combines an ordered additive secret sharing algorithm with a unique index permutation method. This approach efficiently outsources medical data while safeguarding both the data itself and access patterns from potential leakage. Our experimental results demonstrate ECMO's efficiency and scalability, with a single store operation containing 500 keywords taking only <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$42.5 \;\mu s$</tex-math></inline-formula> on average.

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Publication Details

Journal
IEEE Open Journal of the Computer Society
Published
2024-11-25
DOI
https://doi.org/10.1109/ojcs.2024.3506114
Citations
2
Primary Topic
Wireless Body Area Networks
Type
article
Field-Weighted Citation Impact
0.37
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article

ECMO: An Efficient and Confidential Outsourcing Protocol for Medical Data

Xiangyi Meng, Yuefeng Du, Cong Wang
2 citations
IEEE Open Journal of the Computer Society
Wireless Body Area Networks
0.37
article

ECMO: An Efficient and Confidential Outsourcing Protocol for Medical Data

Xiangyi Meng, Yuefeng Du, Cong Wang
article en
2 citations

Abstract

Cloud computing has significantly advanced medical data storage capabilities, enabling healthcare institutions to outsource data management. However, this shift introduces critical security and privacy risks, as sensitive patient information is stored on untrusted third-party servers. Existing cryptographic solutions, such as searchable encryption, offer some security guarantees but struggle with challenges like leakage-based attacks, high computational overhead, and limited scalability. To address these limitations in medical data outsourcing, we present ECMO, a novel protocol that combines an ordered additive secret sharing algorithm with a unique index permutation method. This approach efficiently outsources medical data while safeguarding both the data itself and access patterns from potential leakage. Our experimental results demonstrate ECMO's efficiency and scalability, with a single store operation containing 500 keywords taking only <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$42.5 \;\mu s$</tex-math></inline-formula> on average.

IEEE Open Journal of the Computer SocietyVol. 6
City University of Hong Kong (HK)
Openalex Percentile: Top 42%
Wireless Body Area Networks
0.37
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