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The Influencing Factors of Computer Network Security in Universities

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DOI: 10.23977/infkm.2022.030109 | Downloads: 9 | Views: 597

Author(s)

Juan Wu 1,2, Dexi Chen 1,2, Haiqing Liu 3

Affiliation(s)

1 School of Computer and Big Data, Jining Normal University, Wulanchabu, Inner Mongolia, China
2 Philippine Christian University Center for International Education, Manila, Philippine
3 Jining District Experimental Middle School, Wulanchabu, Inner Mongolia, China

Corresponding Author

Juan Wu

ABSTRACT

The extensive application of network technology has had a great impact on the economy, and has prompted profound changes in the way of life and production of human society. In the field of education, it has also caused profound changes. College computer network security has become an important part of national network security construction around the world. The computer network in colleges and universities has become a powerful tool for the external publicity and communication of the school. The improvement of the student network in the campus network has gradually become the main improvement point of the campus network security. The purpose of this paper is to analyze the factors that affect the security of college computer networks. The experimental results show that the interviewed teenagers are more inclined to solve their difficulties in life and study through online search channels, although some search software may contain certain network risks.

KEYWORDS

Computer Network, Campus Network Security, Key Technologies, Influencing Factors

CITE THIS PAPER

Juan Wu, Dexi Chen, Haiqing Liu, The Influencing Factors of Computer Network Security in Universities. Information and Knowledge Management (2022) Vol. 3: 57-63. DOI: http://dx.doi.org/10.23977/infkm.2022.030109.

REFERENCES

[1] Razali M F, Rusli M E, Jamil N, et al. TPAL: A Protocol for Node Authentication in IoT [J]. Journal of computer sciences, 2018, 14(10):1401-1411.
[2] Neville U, Foley S N. Reasoning about firewall policies through refinement and composition [J]. Journal of Computer Security, 2018, 26(2):207-254.
[3] Pachghare V K, Kulkarni P, Nikam D M. Overview of Intrusion Detection Systems [J]. International Journal of Computational I, 2018, 13(2):197-200.
[4] Ghuraify H, Al-Bakry A A, Al-Jayashi A T. Dual Security Using Image Steganography Based Matrix Partition [J]. International Journal of Network Security & Its Applications, 2019, 11(2):13-31.
[5] Lee S, Shin S H, Roh B H. Classification of Freenet Traffic Flow Based on Machine Learning [J]. Journal of Communications, 2018, 13(11):654-660.
[6] Ramadhan M K, Al-Rammahi A. Image Cryptography with Least Squares Approximations [J]. Journal of computer sciences, 2019, 15(11):1659-1668.
[7] Sivamani S, Choi J, Bae K, et al. A smart service model in greenhouse environment using event-based security based on wireless sensor network [J]. Concurrency & Computation, 2018, 30(1):1-11.
[8] Abdulhammed R, Faezipour M, Abuzneid A, et al. Deep and Machine Learning Approaches for Anomaly-Based Intrusion Detection of Imbalanced Network Traffic [J]. IEEE Sensors Letters, 2019, 3(1):1-4.
[9] Tibi M H, Ganayem A N, Asad K. The privacy paradox in using Facebook among Arab teens: between declarations and behaviour [J]. International journal of information privacy, security and integrity, 2018, 3(4):310-326.
[10] Tsitaitse T J, Cai Y, Suntu S L. Secure Roaming Authentication Mechanism for Wi-Fi Based Networks [J]. International Journal of Innovative Computing Information and Control, 2018, 14(6):2221-2243.

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