Abstract
With the rapid development of the Internet technology, data security is becoming more and more important. Data encryption is an important means to protect data security. AES is an important algorithm for encrypting data. However, when the amount of data needed to be encrypted is large, the traditional AES algorithm runs very slowly. This paper presents a parallel AES encryption algorithm based on MapReduce architecture, which can be applied in large-scale cluster environment. It can improve the efficiency of massive data encryption and decryption by parallelization. And the paper designs a parallel cipher block chaining mode to apply AES algorithm. Experiments show that the proposed algorithm has good scalability and efficient performance, and can be applied to the security of massive data in cloud computing environment.
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References
Fernandes, D.A.B., Soares, L.F.B., Gomes, J.V., et al.: Security issues in cloud environments: a survey. Int. J. Inf. Secur. 13(2), 113–170 (2014)
Ahuja, S.P., Komathukattil, D.: A survey of the state of cloud security. Netw. Commun. Technol. 1(2), 66–75 (2012)
Wu, W.L., Feng, D.G.: The State-of-the-art of research on block cipher mode of operation. Chin. J. Comput. 29(1), 21–36 (2006)
Qing, S.H.: Construction of parallel cryptographic systems. J. Softw. 11(10), 1286–1293 (2000)
Yin, X.C., Chen, W.H., Xie, L.: Parallel processing model of the block cipher. J. Chin. Comput. Syst. 26(4), 600–603 (2005)
Yang, J., Ge, W., Cao, P., et al.: An area-efficient design of reconfigurable s-box for parallel implementation of block ciphers. IEICE Electron. Express 13(11), 1–9 (2016)
Lee, W.K., Cheong, H.S., Phan Raphael, C.W., et al.: Fast implementation of block ciphers and PRNGs in maxwell GPU architecture. Cluster Comput. 19(1), 335–347 (2016)
Dean, J., Ghemawat, S.: MapReduce: a flexible data processing tool. Commun. ACM 53, 72–77 (2010)
Dean, J., Ghemawat, S.: MapReduce: simplified data processing on large clusters. Commun. ACM 51(1), 107–113 (2008)
White, T.: Hadoop the Definitive Guide. O’Reilly, USA (2009)
Landset, S., Khoshgoftaar, T.M., Richter, A.N., et al.: A survey of open source tools for machine learning with big data in the Hadoop ecosystem. J. Big Data 2(1), 1–36 (2015)
Acknowledgements
This work was supported by the National Natural Science Foundation of China (No. 61702345).
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Shi, J., Wang, S., Sun, L. (2020). A Parallel AES Encryption Algorithms and Its Application. In: Atiquzzaman, M., Yen, N., Xu, Z. (eds) Big Data Analytics for Cyber-Physical System in Smart City. BDCPS 2019. Advances in Intelligent Systems and Computing, vol 1117. Springer, Singapore. https://doi.org/10.1007/978-981-15-2568-1_24
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DOI: https://doi.org/10.1007/978-981-15-2568-1_24
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