A Big Data Encryption Method based on Lorenz and Feistel Structures
Yanghao Wu, Xiaohan Huang, Jiaxi Liu, Liang Chang · 2022 International Conference on Computer Engineering and Artificial Intelligence (ICCEAI) · 2022
With the development of information technology, the information network has entered the era of big data. The dissemination and storage of a large amount of data will not only create value, but also increase the risk of data leakage. Data privacy protection is an important research topic in the field of network security, and the existing encryption methods make it difficult to give attention to the confidentiality and efficiency of big data encryption at the same time. Therefore, this paper proposes a hybrid encryption method based on the Lorenz system and Feistel structure, which is applied to large data encryption. It takes advantage of the randomness of a chaotic system, the confidentiality of hybrid encryption, and the high efficiency of symmetric encryption to ensure the speed and security of large data encryption at the same time.