Bidirectional Identity-Based Inner-Product Functional Re-Encryption in Vaccine Data Sharing

With the development of cloud computing, more and more data is stored in cloud servers, which leads to an increasing degree of privacy of data stored in cloud servers. For example, in the critical domain of medical vaccine trials, where public health outcomes hinge on the analysis of sensitive patient data, the imperative to safeguard privacy has never been more pronounced. Traditional encryption methods, though effective at protecting data, often expose vulnerabilities during decryption and lack the ability to support granular data access and computation. One-way re-encryption schemes further impede the agility of data sharing, which is indispensable for the collaborative efforts of research institutions. To address these limitations, we propose a novel bidirectional re-encryption scheme for inner-product functional encryption (IPFE). Our scheme secures data while allowing computation and sharing in an encrypted state, preserving patient privacy without hindering research. By harnessing inner-product functional encryption, our approach allows authorized researchers to extract valuable insights from encrypted data, significantly enhancing privacy protections. Our scheme’s security is predicated on the <inline-formula><tex-math notation="LaTeX">$l$</tex-math></inline-formula>-ABDHE (augmented bilinear Diffie-Hellman exponent) assumption, ensuring robustness against chosen plaintext attacks within the standard model. This foundation not only secures the data but also yields compact ciphertext length, minimizing storage demands. We introduce a protocol specifically designed for medical vaccine trials, which leverages our bidirectional IB-IPFRE (Identity-Based Inner-Product Functional Re-Encryption) scheme. This protocol enhances data security, supports collaborative research, and maintains patient privacy. Its application in vaccine trials demonstrates the scheme’s effectiveness in protecting sensitive information while enabling critical research insights.

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Publication Details

Journal
IEEE Transactions on Cloud Computing
Published
2025-03-19
DOI
https://doi.org/10.1109/tcc.2025.3552740
Primary Topic
Big Data and Digital Economy
Type
article
Field-Weighted Citation Impact
0.00
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article

Bidirectional Identity-Based Inner-Product Functional Re-Encryption in Vaccine Data Sharing

Bo Yang, Yanwei Zhou, Zhiquan Liu, Mingwu Zhang et al.
IEEE Transactions on Cloud Computing
Big Data and Digital Economy
article

Bidirectional Identity-Based Inner-Product Functional Re-Encryption in Vaccine Data Sharing

Bo Yang, Yanwei Zhou, Zhiquan Liu, Mingwu Zhang, Jing Wang, Yasi Zhu
article en

Abstract

With the development of cloud computing, more and more data is stored in cloud servers, which leads to an increasing degree of privacy of data stored in cloud servers. For example, in the critical domain of medical vaccine trials, where public health outcomes hinge on the analysis of sensitive patient data, the imperative to safeguard privacy has never been more pronounced. Traditional encryption methods, though effective at protecting data, often expose vulnerabilities during decryption and lack the ability to support granular data access and computation. One-way re-encryption schemes further impede the agility of data sharing, which is indispensable for the collaborative efforts of research institutions. To address these limitations, we propose a novel bidirectional re-encryption scheme for inner-product functional encryption (IPFE). Our scheme secures data while allowing computation and sharing in an encrypted state, preserving patient privacy without hindering research. By harnessing inner-product functional encryption, our approach allows authorized researchers to extract valuable insights from encrypted data, significantly enhancing privacy protections. Our scheme’s security is predicated on the <inline-formula><tex-math notation="LaTeX">$l$</tex-math></inline-formula>-ABDHE (augmented bilinear Diffie-Hellman exponent) assumption, ensuring robustness against chosen plaintext attacks within the standard model. This foundation not only secures the data but also yields compact ciphertext length, minimizing storage demands. We introduce a protocol specifically designed for medical vaccine trials, which leverages our bidirectional IB-IPFRE (Identity-Based Inner-Product Functional Re-Encryption) scheme. This protocol enhances data security, supports collaborative research, and maintains patient privacy. Its application in vaccine trials demonstrates the scheme’s effectiveness in protecting sensitive information while enabling critical research insights.

IEEE Transactions on Cloud ComputingVol. 13(2)
Jinan University (CN), Hubei University of Technology (CN), Shaanxi Normal University (CN)
Zero hunger
Openalex Percentile: Top 94%
Big Data and Digital Economy
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