Efficient and Privacy-Preserving Categorization for Encrypted EMR
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 suppo...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2023-02-01
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| Series: | Mathematics |
| Subjects: | |
| Online Access: | https://www.mdpi.com/2227-7390/11/3/754 |
| _version_ | 1797623806230003712 |
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| author | Zhiliang Zhao Shengke Zeng Shuai Cheng Fei Hao |
| author_facet | Zhiliang Zhao Shengke Zeng Shuai Cheng Fei Hao |
| author_sort | Zhiliang Zhao |
| collection | DOAJ |
| description | 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. |
| first_indexed | 2024-03-11T09:33:58Z |
| format | Article |
| id | doaj.art-0ab6fdbd6ec348948cb513aa2996032d |
| institution | Directory Open Access Journal |
| issn | 2227-7390 |
| language | English |
| last_indexed | 2024-03-11T09:33:58Z |
| publishDate | 2023-02-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Mathematics |
| spelling | doaj.art-0ab6fdbd6ec348948cb513aa2996032d2023-11-16T17:24:05ZengMDPI AGMathematics2227-73902023-02-0111375410.3390/math11030754Efficient and Privacy-Preserving Categorization for Encrypted EMRZhiliang Zhao0Shengke Zeng1Shuai Cheng2Fei Hao3School of Computer and Software Engineering, Xihua University, Chengdu 610039, ChinaSchool of Computer and Software Engineering, Xihua University, Chengdu 610039, ChinaSchool of Computer and Software Engineering, Xihua University, Chengdu 610039, ChinaSchool of Computer Science, Shaanxi Normal University, Xi’an 710119, ChinaElectronic 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.https://www.mdpi.com/2227-7390/11/3/754electronic health recordpublic key encryption with equality testprivacy protectiongroup-based applicationguessing attack |
| spellingShingle | Zhiliang Zhao Shengke Zeng Shuai Cheng Fei Hao Efficient and Privacy-Preserving Categorization for Encrypted EMR Mathematics electronic health record public key encryption with equality test privacy protection group-based application guessing attack |
| title | Efficient and Privacy-Preserving Categorization for Encrypted EMR |
| title_full | Efficient and Privacy-Preserving Categorization for Encrypted EMR |
| title_fullStr | Efficient and Privacy-Preserving Categorization for Encrypted EMR |
| title_full_unstemmed | Efficient and Privacy-Preserving Categorization for Encrypted EMR |
| title_short | Efficient and Privacy-Preserving Categorization for Encrypted EMR |
| title_sort | efficient and privacy preserving categorization for encrypted emr |
| topic | electronic health record public key encryption with equality test privacy protection group-based application guessing attack |
| url | https://www.mdpi.com/2227-7390/11/3/754 |
| work_keys_str_mv | AT zhiliangzhao efficientandprivacypreservingcategorizationforencryptedemr AT shengkezeng efficientandprivacypreservingcategorizationforencryptedemr AT shuaicheng efficientandprivacypreservingcategorizationforencryptedemr AT feihao efficientandprivacypreservingcategorizationforencryptedemr |