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Efficient and Privacy-Preserving Categorization for Encrypted EMR

Authors :
Zhiliang Zhao
Shengke Zeng
Shuai Cheng
Fei Hao
Source :
Mathematics, Vol 11, Iss 3, p 754 (2023)
Publication Year :
2023
Publisher :
MDPI AG, 2023.

Abstract

Electronic Health Records (EHRs) must be encrypted for patient privacy; however, an encrypted EHR is a challenge for the administrator to categorize. In addition, EHRs are predictable and possible to be guessed, although they are in encryption style. In this work, we propose a secure scheme to support the categorization of encrypted EHRs, according to some keywords. In regard to the predictability of EHRs, we focused on guessing attacks from not only the storage server but also the group administrator. The experiment result shows that our scheme is efficient and practical.

Details

Language :
English
ISSN :
22277390
Volume :
11
Issue :
3
Database :
Directory of Open Access Journals
Journal :
Mathematics
Publication Type :
Academic Journal
Accession number :
edsdoj.0ab6fdbd6ec348948cb513aa2996032d
Document Type :
article
Full Text :
https://doi.org/10.3390/math11030754