Vol.31, No.1, 2022, pp.13-28, doi:10.32604/iasc.2022.019121
Cyber-Attack Detection and Mitigation Using SVM for 5G Network
  • Sulaiman Yousef Alshunaifi, Shailendra Mishra*, Mohammed Alshehri
Department of Information Technology, College of Computer and Information Sciences Majmaah University, Majmaah, 11952, Saudi Arabia
* Corresponding Author: Shailendra Mishra. Email:
Received 03 April 2021; Accepted 05 May 2021; Issue published 03 September 2021
5G technology is widely seen as a game-changer for the IT and telecommunications sectors. Benefits expected from 5G include lower latency, higher capacity, and greater levels of bandwidth. 5G also has the potential to provide additional bandwidth in terms of AI support, further increasing the benefits to the IT and telecom sectors. There are many security threats and organizational vulnerabilities that can be exploited by fraudsters to take over or damage corporate data. This research addresses cybersecurity issues and vulnerabilities in 4G(LTE) and 5G technology. The findings in this research were obtained by using primary and secondary data. Secondary data was collected by reviewing literature and conducting surveys. Primary data were obtained by conducting an experimental simulation using the support vector machine (SVM) approach. The results show that cybersecurity issues related to 4G and 5G need to be addressed to ensure integrity, confidentiality, and availability. All enterprises are constantly exposed to a variety of risks. Also implemented an efficient SVM-based attack detection and mitigation system for 5G network. The proposed intrusion detection system defends against security attacks in the 5G environment. The results show that the throughput and intrusion detection rate is higher while the latency, energy consumption, and packet loss ratio are low, indicating that the proposed intrusion detection and defense system has achieved better QoS. The security solutions are fast and effective in detecting and mitigating cyber-attacks.
Cybersecurity; cyberattack; vulnerability; threat; SVM; IDS
Cite This Article
Alshunaifi, S. Y., Mishra, S., Abdul, M. (2022). Cyber-Attack Detection and Mitigation Using SVM for 5G Network. Intelligent Automation & Soft Computing, 31(1), 13–28.
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