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Traceable and undeniable ciphertext-policy attribute-based encryption for cloud storage service

Author

Listed:
  • Gang Yu
  • Yongjuan Wang
  • Zhenfu Cao
  • Jian Lin
  • Xiangyu Wang

Abstract

Ciphertext-policy attribute-based encryption is a promising mechanism with fine-grained access control for cloud storage system. However, there is a long-lasting problem of key abuse that a user may share its decryption key and a semi-honest authority may illegally issue decryption keys for unauthorized users for profits. To address this problem, we propose an accountable ciphertext-policy attribute-based encryption scheme. In our construction, there are two authorities to issue keys for users, but they cannot decrypt any ciphertexts without collusion. A shared key can be effectively traced, and if the traced identity claims that it is innocent, an auditor can publicly audit who will be responsible for the shared key. Compared with existing accountable ciphertext-policy attribute-based encryption schemes, the proposed scheme is more practical from the two aspects: (1) a user can normally request for a decryption key along with a short signature, and no additional interaction between users and authorities is needed; and (2) the complexity of tracing a masked secret key is reduced to | U | exponent computation, where | U | denotes the number of users in the system. At last, we give the security and experimental analysis.

Suggested Citation

  • Gang Yu & Yongjuan Wang & Zhenfu Cao & Jian Lin & Xiangyu Wang, 2019. "Traceable and undeniable ciphertext-policy attribute-based encryption for cloud storage service," International Journal of Distributed Sensor Networks, , vol. 15(4), pages 15501477198, April.
  • Handle: RePEc:sae:intdis:v:15:y:2019:i:4:p:1550147719841276
    DOI: 10.1177/1550147719841276
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    Cited by:

    1. Yuting Zuo & Zhaozhe Kang & Jian Xu & Zhide Chen, 2021. "BCAS: A blockchain-based ciphertext-policy attribute-based encryption scheme for cloud data security sharing," International Journal of Distributed Sensor Networks, , vol. 17(3), pages 15501477219, March.

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