Abstract
The emerging attribute-based access control (ABAC) mechanism is an expressive, flexible, and manageable authorization technique that is particularly suitable for current distributed, inconstant and complex service-oriented scenarios. Unfortunately, the inevitable disclosure of attributes that carry sensitive information bring significant risks to users’ privacy, which obstructs the further development and popularization of the ABAC severely. In this paper, we propose an effective privacy-preserving ABAC (P-ABAC) scheme to defend against privacy leakage risks of users’ attributes. In the P-ABAC approach, the necessary sensitive attributes are securely handled on the service requester side by using the homomorphic encryption method for privacy protection. And meanwhile, the service provider is still able to make accurate access decisions according to the received attribute ciphertext and pre-set policies with the help of the homomorphic encryption-based secure multi-party computation techniques, while learning no privacy information. The theoretical analysis proves that our model contributes to making an efficient and effective ABAC model with the enhanced privacy-protection feature.
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Notes
- 1.
Note that the authenticity and accuracy of the submitted attributes can be guaranteed with the supports of digital signature and terminal-oriented trusted computing techniques, which are orthogonal to our work and out of the scope of this paper.
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Acknowledgments
This work was supported by the National Natural Science Foundation of China under Grants 61702561, 61702562, and 61632009, the Hunan Provincial Innovation Foundation for Postgraduate under Grant CX2015B047, and the Guangdong Provincial Natural Science Foundation under Grant 2017A030308006.
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Xu, Y., Zeng, Q., Wang, G., Zhang, C., Ren, J., Zhang, Y. (2018). A Privacy-Preserving Attribute-Based Access Control Scheme. In: Wang, G., Chen, J., Yang, L. (eds) Security, Privacy, and Anonymity in Computation, Communication, and Storage. SpaCCS 2018. Lecture Notes in Computer Science(), vol 11342. Springer, Cham. https://doi.org/10.1007/978-3-030-05345-1_31
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