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Data Security for Cloud Datasets With Bloom Filters on Ciphertext Policy Attribute Based Encryption
Abstract
Cloud data storage environments allow the data providers to store and share large amounts of datasets generated from various resources. However, outsourcing private data to a cloud server is insecure without an efficient access control strategy. Thus, it is important to protect the data and privacy of user with a fine-grained access control policy. In this article, a Bloom Filter-based Ciphertext-Policy Attribute-Based Encryption (BF-CP-ABE) technique is presented to provide data security to cloud datasets with a Linear Secret Sharing Structure (LSSS) access policy. This fine-grained access control scheme hides the whole attribute set in the ciphertext, whereas in previous CP-ABE methods, the attributes are partially hidden in the ciphertext which in turn leaks private information about the user. Since the attribute set of the BF-CP-ABE technique is hidden, bloom filters are used to identify the authorized users during data decryption. The BF-CP-ABE technique is designed to be selective secure under an Indistinguishable-Chosen Plaintext attack and the simulation results show that the communication overhead is significantly reduced with the adopted LSSS access policy.
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