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Personalized Privacy-Preserving Medical Data Sharing for Blockchain-based Smart Healthcare Networks

conference contribution
posted on 2022-11-28, 22:47 authored by Y Qu, S Chen, Longxiang GaoLongxiang Gao, L Cui, Keshav SoodKeshav Sood, S Yu
With the growing proliferation of intelligent end devices and data analytics techniques, real momentum towards the development of smart healthcare networks (SHN) has already been evident. Multiple parties in SHNs continuously exchange medical data in order to achieve a precise diagnosis and process optimization. Privacy issue emerges since medical data are susceptible, while the combination of a series of medical data may lead to further privacy leakage. Adversaries launch unceasingly launch poisoning attacks, a dominant attack to maliciously manipulate data, severely impact the authenticity of the data transmitting over the SHNs, leading to misdiagnosing or even physical damage. In this paper, we propose a personalized differential privacy model built upon blockchain, in which the community density is exploited to customize the degree of privacy protection and inject corresponding noise data. Besides using blockchain as the underlying network architecture to defeat poisoning attacks. The proposed model can guarantee the authentication of the differentially private data, traceability of data, and single-point failure avoidance in SHN. Evaluation and extensive results using real-world data sets demonstrate the superiority of the proposed model.

History

Volume

2022-May

Pagination

4229-4234

Start date

2022-05-16

End date

2022-05-20

ISSN

1550-3607

ISBN-13

9781538683477

Publication classification

E1 Full written paper - refereed

Title of proceedings

IEEE International Conference on Communications

Event

ICC 2022 - IEEE International Conference on Communications

Publisher

IEEE

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