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 crypt...
Saved in:
| Main Authors: | , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
IEEE
2025-01-01
|
| Series: | IEEE Open Journal of the Computer Society |
| Subjects: | |
| Online Access: | https://ieeexplore.ieee.org/document/10767272/ |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1841550777565315072 |
|---|---|
| author | Xiangyi Meng Yuefeng Du Cong Wang |
| author_facet | Xiangyi Meng Yuefeng Du Cong Wang |
| author_sort | Xiangyi Meng |
| collection | DOAJ |
| description | 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><tex-math notation="LaTeX">$42.5 \;\mu s$</tex-math></inline-formula> on average. |
| format | Article |
| id | doaj-art-7f1ef7dbf0a248118f8e70a4777f2477 |
| institution | Kabale University |
| issn | 2644-1268 |
| language | English |
| publishDate | 2025-01-01 |
| publisher | IEEE |
| record_format | Article |
| series | IEEE Open Journal of the Computer Society |
| spelling | doaj-art-7f1ef7dbf0a248118f8e70a4777f24772025-01-10T00:03:31ZengIEEEIEEE Open Journal of the Computer Society2644-12682025-01-016374810.1109/OJCS.2024.350611410767272ECMO: An Efficient and Confidential Outsourcing Protocol for Medical DataXiangyi Meng0https://orcid.org/0000-0003-0863-473XYuefeng Du1https://orcid.org/0000-0003-1091-6832Cong Wang2https://orcid.org/0000-0003-0547-315XCity University of Hong Kong, Hong Kong, ChinaCity University of Hong Kong, Hong Kong, ChinaCity University of Hong Kong, Hong Kong, ChinaCloud 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><tex-math notation="LaTeX">$42.5 \;\mu s$</tex-math></inline-formula> on average.https://ieeexplore.ieee.org/document/10767272/Additive secret sharingcloud storageindex permutationmedical data outsourcing |
| spellingShingle | Xiangyi Meng Yuefeng Du Cong Wang ECMO: An Efficient and Confidential Outsourcing Protocol for Medical Data IEEE Open Journal of the Computer Society Additive secret sharing cloud storage index permutation medical data outsourcing |
| title | ECMO: An Efficient and Confidential Outsourcing Protocol for Medical Data |
| title_full | ECMO: An Efficient and Confidential Outsourcing Protocol for Medical Data |
| title_fullStr | ECMO: An Efficient and Confidential Outsourcing Protocol for Medical Data |
| title_full_unstemmed | ECMO: An Efficient and Confidential Outsourcing Protocol for Medical Data |
| title_short | ECMO: An Efficient and Confidential Outsourcing Protocol for Medical Data |
| title_sort | ecmo an efficient and confidential outsourcing protocol for medical data |
| topic | Additive secret sharing cloud storage index permutation medical data outsourcing |
| url | https://ieeexplore.ieee.org/document/10767272/ |
| work_keys_str_mv | AT xiangyimeng ecmoanefficientandconfidentialoutsourcingprotocolformedicaldata AT yuefengdu ecmoanefficientandconfidentialoutsourcingprotocolformedicaldata AT congwang ecmoanefficientandconfidentialoutsourcingprotocolformedicaldata |