Machine Learning Assisted Security Analysis of 5G-Network-Connected Systems

TL;DR

This paper introduces a machine learning-based security analysis framework for 5G core networks, identifying numerous new vulnerabilities and attack vectors, including novel exploits and security loopholes in popular applications like WhatsApp.

Contribution

It presents a novel approach using attack graphs and machine learning to analyze 5G network vulnerabilities, revealing 119 new exploits and complex attack vectors.

Findings

119 novel exploits identified in 5G core network

Five new attacks on 5G Authentication and Key Agreement protocol

Four security loopholes found in WhatsApp on 5G

Abstract

The core network architecture of telecommunication systems has undergone a paradigm shift in the fifth-generation (5G)networks. 5G networks have transitioned to software-defined infrastructures, thereby reducing their dependence on hardware-based network functions. New technologies, like network function virtualization and software-defined networking, have been incorporated in the 5G core network (5GCN) architecture to enable this transition. This has resulted in significant improvements in efficiency, performance, and robustness of the networks. However, this has also made the core network more vulnerable, as software systems are generally easier to compromise than hardware systems. In this article, we present a comprehensive security analysis framework for the 5GCN. The novelty of this approach lies in the creation and analysis of attack graphs of the software-defined and virtualized 5GCN through machine learning. This analysis points to 119 novel possible exploits in the 5GCN. We demonstrate that these possible exploits of 5GCN vulnerabilities generate five novel attacks on the 5G Authentication and Key Agreement protocol. We combine the attacks at the network, protocol, and the application layers to generate complex attack vectors. In a case study, we use these attack vectors to find four novel security loopholes in WhatsApp running on a 5G network.