Homomorphic Encryption Based Privacy-Preservation for IoMT
Open accessAbstract
Healthcare applications store private user data on cloud servers and perform computation operations that support several patient diagnoses. Growing cyber-attacks on hospital systems result in user data being held at ransom. Furthermore, mathematical operations on data stored in the Cloud are exposed to untrusted external entities that sell private data for financial gain. In this paper, we propose a privacy-preserving scheme using homomorphic encryption to secure medical plaintext data from being accessed by attackers. Secret sharing distributes computations to several virtual nodes on the edge and masks all arithmetic operations, preventing untrusted cloud servers from learning the tasks performed on the encrypted patient data. Virtual edge nodes benefit from cloud computing resources to accomplish computing-intensive mathematical functions and reduce latency in device–edge node data transmission. A comparative analysis with existing studies demonstrates that homomorphically encrypted data stored at the edge preserves data privacy and integrity. Furthermore, secret sharing-based multi-node computation using virtual nodes ensures data confidentiality from untrusted cloud networks.
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Securing data security while transferring susceptible data from one node to another remains a difficult task.
“Furthermore, securing data security while transferring susceptible data from one node to another remains a difficult task [204].”
From Federated learning-based AI approaches in smart healthcare: Concepts, taxonomies, challenges and open issues (2023) · cites this paper as [204]
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- Authors
- Salim, M. M., Kim, I., Doniyor, U., Lee, C., & Park, J. H.
- Affiliations
- Seoul National University of Science and Technology (KR)
- Corresponding author
- Park, Jong Hyuk
- Venue
- Applied Sciences
- Publisher
- MDPI AG
- Published
- 2021-09-20
- Volume
- 11
- Issue
- 18
- Pages
- 8757
- ISSN
- 2076-3417 (ISSN-L)
- OpenAlex
- W3203898451
- Cited by
- 57
- References
- 21
- Citations by year
- 2026: 6 · 2025: 17 · 2024: 12 · 2023: 14 · 2022: 7 · 2021: 1
- FWCI
- 3.01
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Licence
- Locations
- Applied Sciences (publishedVersion, cc-by)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
- Funders
- National Research Foundation of Korea (2019M3F2A1073386)
- Topics
- Physical Sciences › Computer Science › Artificial Intelligence › Cryptography and Data Security
- Physical Sciences › Computer Science › Information Systems › Cloud Data Security Solutions
- Physical Sciences › Computer Science › Computer Networks and Communications › IoT and Edge/Fog Computing
- Keywords
- homomorphic encryption, privacy preservation, Internet of Medical Things, healthcare data security, secret sharing, edge computing, cloud computing, untrusted cloud servers, data confidentiality, medical data protection
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