An Efficient and Fine-grained Big Data Access Scheme with Privacy-Preserving Policy

Abstract

How to control the access of the huge amount of big data becomes a very
challenging issue, especially when big data are stored in the cloud. Ciphertext-Policy
Attribute based Encryption (CP-ABE) is a promising encryption technique that enables endusers
to encrypt their data under the access policies defined over some attributes of data
consumers and only allows data consumers whose attributes satisfy the access policies to
decrypt the data. In CP-ABE, the access policy is attached to the ciphertext in plaintext form,
which may also leak some private information about end-users. Existing methods only
partially hide the attribute values in the access policies, while the attribute names are still
unprotected. In this paper, we propose an efficient and fine-grained big data access control
scheme with privacy-preserving policy. Specifically, we hide the whole attribute (rather than
only its values) in the access policies. To assist data decryption, we also design a novel
Attribute Bloom Filter to evaluate whether an attribute is in the access policy and locate the
exact position in the access policy if it is in the access policy. Security analysis and
performance evaluation show that our scheme can preserve the privacy from any LSSS access
policy without employing much overhead.