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Key Derivation Policy for data security and data integrity in cloud computing

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Abstract

Cloud computing is currently emerging as a promising next-generation architecture in the Information Technology (IT) industry and education sector. The encoding process of state information from the data and protection are governed by the organizational access control policies. An encryption technique protects the data confidentiality from the unauthorized access leads to the development of fine-grained access control policies with user attributes. The Attribute-Based Encryption (ABE) verifies the intersection of attributes to the multiple sets. The handling of adding or revoking the users is difficult with respect to changes in policies. The inclusion of multiple encrypted copies for the same key raised the computational cost. This paper proposes an efficient Key Derivation Policy (KDP) for improvement of data security and integrity in the cloud and overcomes the problems in traditional methods. The local key generation process in proposed method includes the data attributes. The secret key is generated from the combination of local keys with the user attribute by a hash function. The original text is recovered from the ciphertext by the decryption process. The key sharing between data owner and user validates the data integrity referred MAC verification process. The proposed efficient KDP with MAC verification analyze the security issues and compared with the Cipher Text–Attribute-Based Encryption (CP-ABE) schemes on the performance parameters of encryption time, computational overhead and the average lifetime of key generation. The major advantage of proposed approach is the updating of public information and easy handling of adding/revoking of users in the cloud.

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Correspondence to P. Senthil Kumari.

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Senthil Kumari, P., Nadira Banu Kamal, A.R. Key Derivation Policy for data security and data integrity in cloud computing. Aut. Control Comp. Sci. 50, 165–178 (2016). https://doi.org/10.3103/S0146411616030032

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  • DOI: https://doi.org/10.3103/S0146411616030032

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