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An Encryption Transmission System for High-speed Private Data Streams in Online Education in the Specialty of “Traffic Engineering”

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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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References

  1. Liu S, He T, Li J, Li Y, Kumar A (2023) An effective learning evaluation method based on text data with real-time attribution - a case study for mathematical class with students of junior middle school in China. ACM Trans Asian Low-Resource Lang Inf Process 22(3):63

    Google Scholar 

  2. Rodic MV, Rodic DD (2020) Plans vs reality: reflections on chemical crystallography online teaching during COVID-19. J Chem Educ 97(9):3038–3041

    Article  Google Scholar 

  3. Gao P, Li J, Liu S (2021) An introduction to key technology in artificial intelligence and big data-driven e-learning and e-education. Mobile Netw Appl 26(5):2123–2126

    Article  Google Scholar 

  4. Ser JD, Sanchez-Medina JJ, Vlahogianni EI (2019) Introduction to the special issue on online learning for big-data driven transportation and mobility. IEEE Trans Intell Transp Syst 20(12):4621–4623

    Article  Google Scholar 

  5. Nechkoska RP, Nechovska DK, Angeleski M (2021) Engaging economics and traffic engineering students in community issues using the multicreation approach. Naše Gospodarstvo/Our Econ 67(3):31–40

    Google Scholar 

  6. Liu Y, Bai JN (2019) Key data encryption protection simulation of complex electronic information system. Comput Simul 36(10):269–272

    Google Scholar 

  7. Han PY, Liu CY, Wang JH, Duan SM, Pan HZ, Fang BX (2020) Research on data encryption system and technology for cloud storage. J Commun 41(08):55–65

    Google Scholar 

  8. Nie Y, Zheng BW, Chai ZL (2022) AES encryption system based on heterogeneous reconfigurable computing. Appl Res Comput 39(07):2143–2148

    Google Scholar 

  9. Wu Z, Bai J, Li DS, Li B, Zeng B, Zhang ZQ (2020) White-box cryptographic video data sharing system based on SM4 algorithm. J Beijing Univ Aeronaut Astronaut 46(09):1660–1669

    Google Scholar 

  10. Li L, Lv Z, Tong X (2019) A dynamic location privacy protection scheme based on cloud storage. Int J Netw Secur 21(5):828–834

    Google Scholar 

  11. Ashenafi MM, Andres-Bray JM, Hutt S (2022) Controlled outputs, full data: A privacy-protecting infrastructure for MOOC data. Brit J Educational Technol 53(4):756–775

    Article  Google Scholar 

  12. Slade S, Prinsloo P, Khalil M (2022) The answer is (not only) technological: Considering student data privacy in learning analytics. Br J Edu Technol 53(4):876–893

    Article  Google Scholar 

  13. Wang Y, Liang X, Hei X (2021) Deep learning data privacy protection based on homomorphic encryption in AIoT. Mobile Inf Syst 2021(2):1–11

    Google Scholar 

  14. Mohammed SJ, Basheer D (2021) From cloud computing security towards homomorphic encryption: A comprehensive review. Telkomnika (Telecommun Comput Electron Control) 19(4):1152–1161

    Article  Google Scholar 

  15. Li M, Wang L, Fan J (2019) Fidelity preserved data hiding in encrypted highly autocorrelated data based on homomorphism and compressive sensing. IEEE Access 7(99):69808–69825

    Article  Google Scholar 

  16. Luo YY, Zhou JZ, Xiong YL (2020) Exploration on rail transit general course education under new engineering science strategy. Urban Mass Transit 23(11):10–13+43

    Google Scholar 

  17. Kibiwott KP, Zhang F, Kimeli VK (2019) Privacy preservation for eHealth big data in cloud accessed using resource-constrained devices: survey. Int J Netw Secur 21(2):312–325

    Google Scholar 

  18. Kaur H, Kumar N, Batra S (2019) ClaMPP: a cloud-based multi-party privacy preserving classification scheme for distributed applications. J Supercomput 75(6):3046–3075

    Article  Google Scholar 

  19. Xie J, Hu K, Zhu M, Guo Y (2020) Bioacoustic signal classification in continuous recordings: Syllable-segmentation vs sliding-window. Expert Syst Appl 152(15):113390

    Article  Google Scholar 

  20. Mi B, Long P, Liu Y (2020) Balancing access control and privacy for data deduplication via functional encryption. Math Probl Eng 2020(4):1–11

    MathSciNet  Google Scholar 

  21. Baker RM, Leonard ME, Milosavljevic BH (2020) The sudden switch to online teaching of an upper-level experimental physical chemistry course: challenges and solutions. J Chem Educ 97(9):3097–3101

    Article  Google Scholar 

  22. Müssig J, Clark A, Hoermann S, Loporcaro G, Loporcaro C, Huber T (2020) Imparting materials science knowledge in the field of the crystal structure of metals in times of online teaching: a novel online laboratory teaching concept with an augmented reality application. J Chem Educ 97(9):2643–2650

    Article  Google Scholar 

  23. Peng C, Zhou X, Liu S (2022) An introduction to artificial intelligence and machine learning for online education. Mobile Netw Appl 27(3):1147–1150

    Article  Google Scholar 

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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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Correspondence to Gautam Srivastava.

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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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