Data Security for Cloud Datasets With Bloom Filters on Ciphertext Policy Attribute Based Encryption

G. Sravan Kumar and A. Sri Krishna
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G. Sravan Kumar: Acharya Nagarjuna University, Guntur, India
A. Sri Krishna: RVR & JC College of Engineering, Guntur, India

International Journal of Information Security and Privacy (IJISP), 2019, vol. 13, issue 4, 12-27

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.

Date: 2019
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