Abstract
With the development of information technology, the high-speed private data stream encryption transmission system is more and more widely used in the field of education. The high-speed private data stream encryption transmission system can realize high-speed and safe data transmission and protect the privacy and security of user data. To protect the security of private data in the online education of specialty “traffic engineering”, an encryption transmission system for high-speed private data stream is designed. After the online education system and core modules of traffic engineering are analyzed, the system framework is designed through the codec module and the high-speed privacy data stream processing control and transmission module. The sliding window segmentation method is used to extract the privacy data in the education system and send it to the coding sub-module. Based on a homomorphic encryption algorithm, a private data stream encryption and decryption model is established. The key encoding is designed by the vector quantization coding method. The private data is authenticated according to the characteristics of the key, and the data encryption transmission is completed through the microcontroller. The experimental results show that the encrypted data of the designed system has only 0.01 Gbit loss, and the encryption time is only 93ms. The data dimension displayed after encryption is relatively scattered, and the distribution probability of encrypted data is between 1500–2000, which can effectively encrypt the private data in the online education system of transportation engineering specialty, and improve the security of high-speed private data flow in the online education system of transportation engineering specialty.
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Hongbin Cao contributed to Writing—Original Draft, Methodology, and Conceptualization; Gautam Srivastava contributed to Conceptualization and Writing—Review and Editing equally.
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Cao, H., Srivastava, G. An Encryption Transmission System for High-speed Private Data Streams in Online Education in the Specialty of “Traffic Engineering”. Mobile Netw Appl 28, 1007–1018 (2023). https://doi.org/10.1007/s11036-023-02196-6
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DOI: https://doi.org/10.1007/s11036-023-02196-6