Published Paper Details:

Due to the complexity and volume, outsourcing ciphertexts to a cloud is deemed to be one of the most effective approaches for big data storage and access. Nevertheless, verifying the access legitimacy of a user and securely updating a ciphertext in the cloud based on a new access policy designated by the data owner are two critical challenges to make cloud-based big data storage practical and effective. Findings from the evaluation show that our approach outperforms current state of the art. We also make available our statistically sound dataset, based on known benchmarks, to the wider research community. this proposed work, a secure and verifiable access control scheme based on the HASHED KEY TECHNIQUE cryptosystem for big data storage in clouds. We first propose a new HASHED KEY TECHNIQUE decryption algorithm to overcome the decryption failures of the original HASHED KEY TECHNIQUE, and then detail our scheme and analyze its correctness, security strengths, and computational efficiency. Our scheme allows the cloud server to efficiently update the ciphertext when a new access policy is specified by the data owner, who is also able to validate the update to counter against cheating behaviors of the cloud. It also enables (i) the data owner and eligible users to effectively verify the legitimacy of a user for accessing the data, and (ii) a user to validate the information provided by other users for correct plaintext recovery. Rigorous analysis indicates that our scheme can prevent eligible users from cheating and resist various attacks such as the collusion attack.In such a system,combined with verifiable computation and encrypt-then-mac mechanism, the data confidentiality, the fine-grained access control and the correctness of the delegated computing results are well guaranteed at the same time. Besides, our scheme achieves security against chosen-plaintext attacks under the k-multilinear Decisional hashed technique. Moreover, an extensive simulation campaign confirms the feasibility and efficiency of the proposed solution.