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http://dx.doi.org/10.6109/jkiice.2022.26.9.1374

Research on security technology to respond to edge router-based network attacks  

Hwang, Seong-Kyu (Department of Information & Commnincation Engg., Chosun College University of Science & Technology)
Abstract
Existing research on security technology related to network attack response has focused on research using hardware network security technology, network attacks that wiretap and wiretap network packets, denial of service attack that consumes server resources to bring down the system, and network by identifying vulnerabilities before attack. It is classified as a scanning attack. In addition, methods for increasing network security, antivirus vaccines and antivirus systems have been mainly proposed and designed. In particular, many users do not fully utilize the security function of the router. In order to overcome this problem, it is classified according to the network security level to block external attacks through layered security management through layer-by-layer experiments. The scope of the study was presented by examining the security technology trends of edge routers, and suggested methods and implementation examples to protect from threats related to edge router-based network attacks.
Keywords
Edge router; network attack; security technology; security function of router;
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  • Reference
1 Bitdefender, Bitdefender IoT Security Platform [Internet]. Available: https://www.bitdefender.com/iot/.
2 Fing, Business Solutions: Device Recognition [Internet]. Available: https://www.fing.com/business/.
3 H. Khelifi, S. Luo, B. Nour, H. Moungla, Y. Faheem, R. Hussain, and A. Ksentini, "Named Data Networking in Vehicular Ad Hoc Networks: State-of-the-Art and Challenges,'' IEEE Communication & Surveys Tutorials, vol. 22, no. 1, pp. 320-351, Mar. 2020   DOI
4 M. Lotfollahi, M. J. Siavoshani, R. S. H. Zade, and M. Saberian, "Deep packet: a novel approach for encrypted traffic classification using deep learning," Soft Computing, vol. 24, no. 3, pp. 1999-2012, May. 2019.
5 S. E. Yang, I. S. Kang, B. O. Go, and H. K. Jung, "A Realtime Traffic Shaping Method for VPN Tunneling on Smart Gateway Supporting IoT," The Journal of Korea Institute of Information and Communication Engineering, vol. 21, no. 6, pp. 1121-1126, Jun. 2017.
6 G. Aceto, D. Ciuonzo, A. Montieri, and A. Pescape, "Mobile Encrypted Traffic Classification Using Deep Learning," in Proceedings of 2018 Network Traffic Measurement and Analysis Conference (TMA), Vienna, Austria, pp.1-8, 2018.
7 M. A. Khan and K. Salah, "Iot security: Review, blockchain solutions, and open challenges," Future Generation Computer Systems, vol. 82, pp. 395- 411, May. 2018.   DOI
8 K. Yang, Q. Li, and L. Sun, "Towards automatic fingerprinting of IoT devices in the cyberspace," Computer Networks, vol. 148, pp. 318-327, Jan. 2019.   DOI