Ensuring attribute privacy protection and fast decryption for outsourced data security in mobile cloud computing

Although many users outsource their various data to clouds, data security and privacy concerns are still the biggest obstacles that hamper the widespread adoption of cloud computing. Anonymous attribute-based encryption (anonymous ABE) enables fine-grained access control over cloud storage and preserves receivers' attribute privacy by hiding attribute information in ciphertexts. However, in existing anonymous ABE work, a user knows whether attributes and a hidden policy match or not only after repeating decryption attempts. And, each decryption usually requires many pairings and the computation overhead grows with the complexity of the access formula. Hence, existing schemes suffer a severe efficiency drawback and are not suitable for mobile cloud computing where users may be resource-constrained. In this paper, we propose a novel technique called match-then-decrypt, in which a matching phase is additionally introduced before the decryption phase. This technique works by computing special components in ciphertexts, which are used to perform the test that if the attribute private key matches the hidden access policy in ciphertexts without decryption. For the sake of fast decryption, special attribute secret key components are generated which allow aggregation of pairings during decryption. We propose a basic anonymous ABE construction, and then obtain a security-enhanced extension based on strongly existentially unforgeable one-time signatures. In the proposed constructions, the computation cost of an attribute matching test is less than one decryption operation, which only needs small and constant number of pairings. Formal security analysis and performance comparisons indicate that the proposed solutions simultaneously ensure attribute privacy and improve decryption efficiency for outsourced data storage in mobile cloud computing. (C) 2016 Elsevier Inc. All rights reserved.