An attribute-based keyword search for m-Health networks

Abstract

m-Health stands for mobile health, where mobile devices are used for collecting and distributing health-related data. As the information related to personal health is sensitive in nature, so it should be encrypted first before storing it at the potentially untrusted servers. However, encryption severely affects basic sharing and search operations. To address these issues, a combination of attribute-based encryption and searchable encryption is devised, which enables secure fine-grained search over encrypted data. But the resultant technique incurs high computational complexity, which makes it unsuitable for resource-constrained mobile devices. So, in order to deploy it to mobile devices, searchable encryption should generate constant size secret keys and ciphertexts. However, in existing attribute-based keyword search (ABKS) schemes, the size of the secret key and the ciphertext is proportional to the number of attributes, thus resulting in linear complexity. In this paper, we have proposed a novel ABKS scheme with constant-size secret keys and ciphertexts, thus further reducing the computational cost. Our scheme uses a ciphertext-policy (CP) design framework and supports an AND gate access structure. Further, the proposed CP-ABKS scheme can be proved secure in the selective security model under augmented multi-sequence of exponents decisional Diffie-Hellman assumption.