Research Article
Adaptive Encryption Model of Internet Public Opinion Information Based on Big Data
@INPROCEEDINGS{10.1007/978-3-030-82562-1_32, author={Yanjing Lu and Jiajuan Fang}, title={Adaptive Encryption Model of Internet Public Opinion Information Based on Big Data}, proceedings={Multimedia Technology and Enhanced Learning. Third EAI International Conference, ICMTEL 2021, Virtual Event, April 8--9, 2021, Proceedings, Part I}, proceedings_a={ICMTEL}, year={2021}, month={7}, keywords={Big data Network public opinion Adaptive encryption Encryption model Logistic mapping}, doi={10.1007/978-3-030-82562-1_32} }- Yanjing Lu
Jiajuan Fang
Year: 2021
Adaptive Encryption Model of Internet Public Opinion Information Based on Big Data
ICMTEL
Springer
DOI: 10.1007/978-3-030-82562-1_32
Abstract
The traditional information encryption model takes advantage of the ergodicity of chaotic system, and processes encryption iteratively for many times. Aiming at the above problems, this paper constructs a big data-based network public opinion information adaptive encryption model. Reptiles are used to collect network public opinion information, and the public opinion information is replaced and diffused. After mining the association rules of public opinion information, the information is encrypted by Logistic mapping, and the encryption model is constructed. Compared with the two traditional encryption models, it is proved that the model has the advantages of good encryption effect, high efficiency and low cost, and can be used widely.
