Abstract
Big data require cloud that provides dynamically expanding data storage accessed through the Internet. The outsourcing data in the cloud for storing makes the user data management easier and reduces the cost of maintaining data. Still organizations are not confident to store their data in the cloud, because of security and privacy concerns. However, existing encryption methods are able to protect data confidentiality, but it has some drawbacks of access patterns can also leak sensitive information. The proposed system uses an Elliptic curve with Diffie–Hellman (ECDH) algorithm for encryption and decryption of data to improve the data security in the cloud. This algorithm reduced the computational complexity and encrypted data efficiently. In experimental analysis, the performance of proposed ECDH is calculated using evaluation parameters such as encryption time, decryption time, computation overhead and key generation time. The proposed ECDH algorithm has approximately 70% better performance in terms of encryption time than existing methods such as RSA, MRSA and MRSAC.
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References
Salem, M.Z., Sabbeh, S.F., Tarek, E.L.: An efficient privacy preserving public auditing mechanism for secure cloud storage. Int. J. Appl. Eng. Res. 12(6), 1093–1101 (2017)
Bhatt Agarwal, R.: A technological review on scheduling algorithm to improve performance of cloud computing environment. Int. J. Innov. Technol. Explor. Eng. (IJITEE) 8(6), 166–172 (2019)
Zhou, L., Varadharajan, V., Hitchens, M.: Trust enhanced cryptographic role-based access control for secure cloud data storage. IEEE Trans. Inf. Forensics Secur. 10(11), 2381–2395 (2015)
Wang, Q., Wang, C., Ren, K., Lou, W., Li, J.: Enabling public auditability and data dynamics for storage security in cloud computing. IEEE Trans. Parallel Distrib. Syst. 22(5), 847–859 (2011)
Panwar, N., Negi, S., Rauthan, M.S., Aggarwal, M.A.Y.A.N.K., Jain, P.: An enhanced scheduling approach with cloudlet migrations for resource intensive applications. J. Eng. Sci. Technol. 13(8), 2299–2317 (2018)
Aggrawal, M., Kumar, N., Kumar, R.: Optimized cost model with optimal disk usage for cloud. In: Aggarwal, V.B., Bhatnagar, V., Mishra, D.K. (eds.) Big Data Analytics, pp. 481–485. Springer, Singapore (2018)
Song, W., Cui, Y., Peng, Z.: A full-text retrieval algorithm for encrypted data in cloud storage applications. In: Li, J., Ji, H., Zhao, D., Feng, Y. (eds.) Natural Language Processing and Chinese Computing, pp. 229–241. Springer, Cham (2015)
Cheng, Y., Wang, Z.Y., Ma, J., Wu, J.J., Mei, S.Z., Ren, J.C.: Efficient revocation in ciphertext-policy attribute-based encryption based cryptographic cloud storage. J. Zhejiang Univ. Sci. C 14(2), 85–97 (2013)
Srisakthi, S. Shanthi, A.P.: Design of a secure encryption model (SEM) for cloud data storage using hadamard transforms. Wirel. Pers. Commun. 100, 1727–1741 (2018)
Wang, W., Chen, L., Zhang, Q.: Outsourcing high-dimensional healthcare data to cloud with personalized privacy preservation. Comput. Netw. 88, 136–148 (2015)
He, X.M., Wang, X.S., Li, D., Hao, Y.N.: Semi-homogenous generalization: improving homogenous generalization for privacy preservation in cloud computing. J. Comput. Sci. Technol 31(6), 1124–1135 (2016)
Liu, H., Ning, H., Xiong, Q., Yang, L.T.: Shared authority based privacy-preserving authentication protocol in cloud computing. IEEE Trans. Parallel Distrib. Syst. 26(1), 241–251 (2015)
Kanna, G.P., Vasudevan, V.: A fully homomorphic–elliptic curve cryptography based encryption algorithm for ensuring the privacy preservation of the cloud data. Clust. Comput. 22, 9561–9569 (2019)
Wang, Z., Cao, C., Yang, N., Chang, V.: ABE with improved auxiliary input for big data security. J. Comput. Syst. Sci. 89, 41–50 (2017)
Yang, K., Han, Q., Li, H., Zheng, K., Su, Z., Shen, X.: An efficient and fine-grained big data access control scheme with privacy-preserving policy. IEEE Internet Things J. 4(2), 563–571 (2017)
Yang, C.Y., Huang, C.T., Wang, Y.P., Chen, Y.W., Wang, S.J.: File changes with security proof stored in cloud service systems. Pers. Ubiquit. Comput. 22(1), 45–53 (2018)
Stergiou, C., Psannis, K.E.: Efficient and secure BIG data delivery in cloud computing. Multimed. Tools Appl. 76(21), 22803–22822 (2017)
Thangavel, M., Varalakshmi, P.: Enhanced DNA and ElGamal cryptosystem for secure data storage and retrieval in cloud. Clust. Comput. 21, 1411–1437 (2018)
He, D., Kumar, N., Wang, H., Wang, L., Choo, K.K.R.: Privacy-preserving certificate less provable data possession scheme for big data storage on cloud. Appl. Math. Comput. 314, 31–43 (2017)
Song, W., Wang, B., Wang, Q., Peng, Z., Lou, W., Cui, Y.: A privacy-preserved full-text retrieval algorithm over encrypted data for cloud storage applications. J. Parallel Distrib. Comput. 99, 14–27 (2017)
Gnanaprakasam, T., Rajivkannan, A.: Optimal Ecc based dual encryption technique for data security in cloud. Int. J. Adv. Eng. Technol. VII(II) (2016)
Tewari, A., Gupta, B.B.: Cryptanalysis of a novel ultra-lightweight mutual authentication protocol for IoT devices using RFID tags. J. Supercomput. 73(3), 1085–1102 (2017)
Gupta, B.B., Agrawal, D.P.: Handbook of research on cloud computing and big data applications in IoT. In: IGI Global. (2019). https://doi.org/10.4018/978-1-5225-8407-0
Olakanmi, O.O., Dada, A.: An efficient privacy-preserving approach for secure verifiable outsourced computing on untrusted platforms. Int. J. Cloud Appl. Comput. (IJCAC) 9(2), 79–98 (2019)
Azad, P., Navimipour, N.J.: An energy-aware task scheduling in the cloud computing using a hybrid cultural and ant colony optimization algorithm. Int. J. Cloud Appl. Comput. (IJCAC) 7(4), 20–40 (2017)
Anbuchelian, S., Sowmya, C.M., Ramesh, C.: Efficient and secure auditing scheme for privacy preserving data storage in cloud. Clust. Comput. (2017). https://doi.org/10.1007/s10586-017-1486-z
Zhang, Y., Yu, J., Hao, R., Wang, C., Ren, K.: Enabling efficient user revocation in identity-based cloud storage auditing for shared big data. IEEE Trans. Depend. Secure Comput. (2018). https://doi.org/10.1109/TDSC.2018.2829880
Yu, J., Ren, K., Wang, C.: Enabling cloud storage auditing with verifiable outsourcing of key updates. IEEE Trans. Inf. Forensics Secur. 11(6), 1362–1375 (2016)
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Subramanian, E.K., Tamilselvan, L. Elliptic curve Diffie–Hellman cryptosystem in big data cloud security. Cluster Comput 23, 3057–3067 (2020). https://doi.org/10.1007/s10586-020-03069-3
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DOI: https://doi.org/10.1007/s10586-020-03069-3