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Blockchain-Based Fair Payment for ABE with Outsourced Decryption

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Abstract

Attribute-based encryption (ABE) is an advanced public-key encryption supporting fine-grained access control and flexible sharing of encrypted data. However, in many real-world scenarios, users working with resource-limited devices have to outsource the decryption task due to its huge computational overhead while the decryption party is usually considered to be untrusted, thus leading to the fact that the verifiability of computation results is as important as the privacy. Fair payment, a solution to ensure the interests of both participants involved (i.e., user and worker), is introduced. Generally, fairness is guaranteed by the public verifiability so that the correctness of outsourced result can be easily judged by a trusted third party (TTP) when dispute occurs, which is called optimistic fairness. To remove the TTP and achieve robust fairness, most existing solutions try to handle the verifiability issue with zero-knowledge proofs (ZKPs) and blockchain. Nonetheless, there has not been a proper and efficient solution to obtain robust fairness in ABE outsourcing decryption (ABE-OD) scenarios. To address this issue, in this paper we propose a blockchain-based fair payment for ABE-OD scheme. In particular, we construct a CP-ABE-OD scheme with both public and private verifiability based on existing generic schemes and employ smart contract to guarantee the payment fairness, integrated by IPFS to solve the task data storage. Theoretical analysis and experimental results show that our scheme is secure and efficient.

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Funding

This work was supported in part by National Natural Science Foundation of China (62002120), Shanghai Rising-Star Program (No.22QA1403800), Innovation Program of Shanghai Municipal Education Commission (2021-01-07-00-08-E00101) and NSFC-ISF Joint Scientific Research Program (61961146004) and the “Digital Silk Road” Shanghai International Joint Lab of Trustworthy Intelligent Software (Grant No. 22510750100).

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Authors and Affiliations

  1. East China Normal University, Shanghai, China

    Linjian Hong, Junqing Gong & Haifeng Qian

  2. Shanghai University of Electric Power, Shanghai, China

    Kai Zhang

  3. CCCC Intelligence Transportation Co., Ltd., Tianjin, China

    Haifeng Qian

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  1. Linjian Hong
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  2. Kai Zhang
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  3. Junqing Gong
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  4. Haifeng Qian
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Correspondence to Junqing Gong.

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Hong, L., Zhang, K., Gong, J. et al. Blockchain-Based Fair Payment for ABE with Outsourced Decryption. Peer-to-Peer Netw. Appl. 16, 312–327 (2023). https://doi.org/10.1007/s12083-022-01406-4

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  • DOI: https://doi.org/10.1007/s12083-022-01406-4

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