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Volume 44 Issue 1
Jan.  2022
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NIU Shufen, SONG Mi, FANG Lizhi, WANG Caifen. Cloud Storage Data Sharing Based on Attribute Encryption in Smart Healthcare[J]. Journal of Electronics & Information Technology, 2022, 44(1): 107-117. doi: 10.11999/JEIT210858
Citation: NIU Shufen, SONG Mi, FANG Lizhi, WANG Caifen. Cloud Storage Data Sharing Based on Attribute Encryption in Smart Healthcare[J]. Journal of Electronics & Information Technology, 2022, 44(1): 107-117. doi: 10.11999/JEIT210858

Cloud Storage Data Sharing Based on Attribute Encryption in Smart Healthcare

doi: 10.11999/JEIT210858
Funds:  The National Natural Science Foundation of China (61562077, 61662069, 61662071, 61772022)
  • Received Date: 2021-08-19
  • Accepted Date: 2021-12-27
  • Rev Recd Date: 2021-12-27
  • Available Online: 2022-01-05
  • Publish Date: 2022-01-10
  • In order to achieve multi-user data search in electronic medical record system, an attribute based searchable encryption scheme is proposed. In this scheme, ciphertext and secure indexes are stored in the medical cloud. When the users want to access the medical data, the attribute-base searchable encryption algorithm is used for data search, and the fine-grained access control is realized. At the same time, ciphertext verification algorithm is introduced into the scheme, it solves the problem of incorrect search results under the semi-honest and curious cloud server models. The scheme uses data deduplication technology to eliminate duplicate data and reduce the storage space of the medical cloud. The scheme also realizes the hiding of access policy, and the privacy security of data users is guaranteed. The security analysis shows that the proposed scheme can well protect the confidentiality of medical data and the anonymity of users. The performance analysis demonstrate that the proposed scheme has better performance; Hence, it is more suitable for many-to-many application scenarios such as smart healthcare. It effectively realizes the sharing of patient electronic medical records between doctors and third-party users without infringing on patient privacy.
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