Encrypted transmission method of sensitive data in energy big data center based on AES algorithm

Rui Ma; Dongge Zhu; Jiangbo Sha; Jia Liu; Qingping Zhang

doi:10.1117/12.2626440

21 December 2021 Encrypted transmission method of sensitive data in energy big data center based on AES algorithm

Rui Ma, Dongge Zhu, Jiangbo Sha, Jia Liu, Qingping Zhang

Proceedings Volume 12156, International Conference on Algorithms, High Performance Computing, and Artificial Intelligence (AHPCAI 2021); 121560M (2021) https://doi.org/10.1117/12.2626440
Event: International Conference on Algorithms, High Performance Computing, and Artificial Intelligence (AHPCAI 2021), 2021, Sanya, China

Abstract

In view of the problems of low security, low efficiency of encryption transmission and high energy consumption of data encryption transmission in traditional methods, an AES based sensitive data encryption transmission method for energy big data center is proposed. The encryption round operation of AES algorithm is used for the encryption round operation result. Based on the encryption round operation result of AES algorithm, the secret key data matrix is generated. When data is encrypted, the data matrix is traversed at any node of the encryption end, and the key data matrix is generated again. On this basis, Zigzag permutation method is used for data transmission to complete data encryption transmission. Experimental results show that the security factor and execution efficiency of the proposed method are higher than those of traditional methods, and the energy consumption of data encryption transmission is the lowest, which indicates that the proposed method can ensure the quality of sensitive data encryption transmission in energy big data center.

Citation Download Citation

Rui Ma, Dongge Zhu, Jiangbo Sha, Jia Liu, and Qingping Zhang "Encrypted transmission method of sensitive data in energy big data center based on AES algorithm", Proc. SPIE 12156, International Conference on Algorithms, High Performance Computing, and Artificial Intelligence (AHPCAI 2021), 121560M (21 December 2021); https://doi.org/10.1117/12.2626440

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