A Secure and Fine-Grained Big Data Access Control Scheme for Cloud-Based Services

Abstract

Cloud computing is the delivery of computing services including servers, storage, databases, networking, software, analytics, and intelligence over the Internet. Nowadays, access control is one of the most critical problems with cloud computing. Ciphertext-Policy Attribute Based Encryption (CP-ABE) is a promising encryption technique that enables end-users 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. This paper proposes an efficient and fine-grained big data access control scheme with privacy-preserving policy. Specifically, it hides the whole attribute (rather than only its values) in the access policies. To assist data decryption, it designs an algorithm called 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. The paper also deals with offline attribute guessing attack. Security analysis and performance evaluation show that this scheme can preserve the privacy from any LSSS access policy without employing much overhead.