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With the deep integration of the Internet of Things (IoT) and cloud computing, cloud-oriented IoT is embraced as an important paradigm for efficiency and productivity. On the other hand, it is also becoming an increasingly attractive target for cybercriminals, who attempt to breach data security and privacy. As a potential and promising solution to secure data, ciphertext-policy attribute-based keyword search (CP-ABKS) can provide both fine-grained keyword search and access control over the encrypted data. However, prior CP-ABKS schemes either fail to support lightweight computation or lack of policy protection. In this paper, with offline computation and inner product encryption, we propose a lightweight CP-ABKS scheme with policy protection, such that the encrypted data can be efficiently retrieved and accessed by data users in a fine-grained manner without leaking any sensitive information. We prove the correctness of the proposed scheme and its security in the standard model under the Decisional Bilinear Diffie-Hellman (DBDH) assumption. We also implement our proposed scheme to demonstrate its efficiency. © 2019 IEEE.
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Year: 2019
Language: English
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WoS CC Cited Count: 0
SCOPUS Cited Count: 4
ESI Highly Cited Papers on the List: 0 Unfold All
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30 Days PV: 0
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