Securing Healthcare Data in IoT: A Study on Homomorphic Encryption

The integration of Internet of Things (IoT) technology in healthcare has revolutionized patient care and medical services. However, the sensitive nature of healthcare data necessitates robust privacy and security measures. Homomorphic Encryption (HE) offers a promising solution by enabling computations on encrypted data without the need for decryption, thus ensuring data privacy throughout its lifecycle. This paper explores the application of homomorphic encryption in IoT healthcare systems and presents a case study demonstrating the practical implementation of HE using Paillier encryption for securing IoT healthcare data. Our findings highlight the feasibility of using HE to achieve secure data aggregation and analysis while maintaining patient confidentiality.

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Publication Details

Published
2024-12-04
DOI
https://doi.org/10.1109/commnet63022.2024.10793287
Citations
1
Primary Topic
Privacy-Preserving Technologies in Data
Type
article
Field-Weighted Citation Impact
0.35
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article

Securing Healthcare Data in IoT: A Study on Homomorphic Encryption

Otmane El Mouaatamid, El Mehdi Loualid, Sarra Erregui
1 citations
Privacy-Preserving Technologies in Data
0.35
article

Securing Healthcare Data in IoT: A Study on Homomorphic Encryption

Otmane El Mouaatamid, El Mehdi Loualid, Sarra Erregui
article en
1 citations

Abstract

The integration of Internet of Things (IoT) technology in healthcare has revolutionized patient care and medical services. However, the sensitive nature of healthcare data necessitates robust privacy and security measures. Homomorphic Encryption (HE) offers a promising solution by enabling computations on encrypted data without the need for decryption, thus ensuring data privacy throughout its lifecycle. This paper explores the application of homomorphic encryption in IoT healthcare systems and presents a case study demonstrating the practical implementation of HE using Paillier encryption for securing IoT healthcare data. Our findings highlight the feasibility of using HE to achieve secure data aggregation and analysis while maintaining patient confidentiality.

Mohammed V University (MA), Chouaib Doukkali University (MA)
Openalex Percentile: Top 31%
Privacy-Preserving Technologies in Data
0.35
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