SDN-based GTP-U Traffic Analysis for 5G Networks Conference

Pineda, D, Harrilal-Parchment, R, Akkaya, K et al. (2023). SDN-based GTP-U Traffic Analysis for 5G Networks . 10.1109/NOMS56928.2023.10154440

cited authors

  • Pineda, D; Harrilal-Parchment, R; Akkaya, K; Perez-Pons, A

abstract

  • 5G networks denote a revolutionary improvement in wireless communication by introducing three service grades: Enhanced Mobile Broadband (eMBB), Ultra-Reliable Low Latency Communications (URLLC), and Massive Machine Type Communications (mMTC). These three service grades represent a cost-efficient solution and enhanced user experience with higher data rates and lower latency. However, at the same time, these aspects can benefit attackers (e.g., by leveraging the support for mMTC) to launch various attacks effectively. mMTC comes with a massive number of unattended Internet of Things (IoT) devices known for having low-security capabilities. One of the biggest security concerns related to IoT is that it increases the chances of internal DDoS attacks, which can disrupt 5G core network services. In this paper, we propose our ongoing work on monitoring the GPRS Tunneling Protocol User Plane (GTP-U) traffic, which is used to transport user data from User Equipment (UE) devices. We offer internal traffic filtering mechanisms using Software Defined Networks (SDN) to block the IoT traffic that appears to be malicious. The proposed approach is implemented in a 5G testbed to evaluate the performance and efficiency of factual scenarios.

publication date

  • January 1, 2023

Digital Object Identifier (DOI)