The Application of AES-SM2 Hybrid Encryption Algorithm in Big Data Security and Privacy Protection

In the times of big data, information security and privacy protection have become important issues facing today's society. To address big data's security and privacy problems, research designs and implements a hybrid encryption method using advanced encryption standard algorithms and standard encryption module 2 algorithms for encryption operations. This method utilizes Advanced Encryption Standard encryption algorithms to encrypt plaintext data without calling any encryption libraries. It improves the key extension method and security analysis of Advanced Encryption Standard algorithms. The experimental results show that by changing one key, the confusion range of the improved Advanced Encryption Standard algorithm is 62 ± 6, while the confusion range of the traditional Advanced Encryption Standard algorithm is 63 ± 7. The encryption time of the RSA algorithm is 16.50ms higher than that of Standard Encryption Module 2. The Advanced Encryption Standard scheme improved by Standard Encryption Module 2+ has the fastest decryption speed, followed by RSA+Advanced Encryption Standard scheme, and finally Standard Encryption Module 2+Advanced Encryption Standard scheme. The hybrid encryption algorithm proposed by the research institute can encrypt sensitive information in big data without leaking plaintext information, effectively protecting sensitive information in big data. This scheme can effectively protect sensitive information in big data and provide new ideas for big data in terms of network security and privacy protection.

@article{Huang2024,
  title     = {The Application of AES-SM2 Hybrid Encryption Algorithm in Big Data Security and Privacy Protection},
  journal   = {International Journal of Advanced Computer Science and Applications},
  volume    = {15},
  number    = {6},
  year      = {2024},
  publisher = {The Science and Information Organization},
  author    = {Pingyun Huang and Guizhou Liao and Jianhong Ren},
  doi       = {10.14569/IJACSA.2024.01506101},
  url       = {https://doi.org/10.14569/IJACSA.2024.01506101}
}