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MPLDS: An integration of CP-ABE and local differential privacy for achieving multiple privacy levels data sharing

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Abstract

In ciphertext-policy attribute-based encryption (CP-ABE), once malicious users successfully decrypt the encrypted data, they can obtain the real original personal privacy data, leading to serious privacy leakages problems. Thus, if the user does not access the original private data but the perturbed data while guaranteeing statistical characteristics, the privacy protection capabilities of CP-ABE will be greatly improved. Motivated by this, an integration of basic CP-ABE and local differential privacy (LDP) or achieving multiple privacy levels data sharing (MPLDS) is constructed to provide double privacy protection for data owners, which is with a relatively lower complexity and higher data utility. To prevent different trusted users from colluding and gaining more privacy beyond their trust levels, a randomized perturbation strategy is elaborately designed for resisting collusion attacks (RCA) while ensuring the fact that the output of RCA perturbation strategy is the same as that of the original perturbation, which has been proved from the theoretical level. Finally, the proposed MPLDS scheme is simulated and verified on both synthetic and real data sets, which indicates that the proposed MPLDS scheme outperforms the existing MPPDS scheme while greatly reducing the complexity.

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Notes

  1. Basic CP-ABE is relative to hierarchical CP-ABE, that is, the basic CP-ABE is non-hierarchical access tree structure.

  2. Semantic security under chosen-plaintext attack (CPA) is modelled by an IND-sAtt-CPA game.

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Authors and Affiliations

  1. School of Electrical and Electronic Engineering, Hubei University of Technology, Wuhan, 430068, People’s Republic of China

    Haina Song

  2. Department of Information and Communication Engineering, Beijing University of Posts and Telecommunications (BUPT), Beijing, 100876, People’s Republic of China

    Xinyu Han, Jie Lv, Tao Luo & Jianfeng Li

Authors
  1. Haina Song
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  2. Xinyu Han
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  3. Jie Lv
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  4. Tao Luo
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  5. Jianfeng Li
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Correspondence to Tao Luo.

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This work was supported in part by the National Key Research and Development Program of China under Grant No. 2019YFC1709200 and No. 2019YFC1709202, and the National Science Foundation of China under Grant No. 61571065.

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Song, H., Han, X., Lv, J. et al. MPLDS: An integration of CP-ABE and local differential privacy for achieving multiple privacy levels data sharing. Peer-to-Peer Netw. Appl. 15, 369–385 (2022). https://doi.org/10.1007/s12083-021-01238-8

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  • DOI: https://doi.org/10.1007/s12083-021-01238-8

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