# Cyber5 Gym: An Integrated Framework for 5G Cybersecurity Training
## 3 Related Work  
In recent years, significant advancements have been made in the development of 5G networks, with particular emphasis on enhancing their security and robustness. The work of [27] developed a 5G testbed designed for evaluating performance and security vulnerabilities in network slices. Utilizing OpenAirInterface [29], this testbed integrates both CN and RAN components, employing the OAI Simulator [30] for the emulation of UE and RAN. Within this framework, network slices are represented by Docker Containers instead of separate network functions. Furthermore, other studies such as [11; 31; 32; 33] conduct a comprehensive analysis of platforms and frameworks for implementing Core Network. Comparing Magma [33], Open5 GS [15], and Free5 GC [34], their study aims to evaluate development and computational efficiency, emphasizing flexibility, scalability, and resource utilization. Their findings motivate us to utilize Open5 GS for the implementation of the CN components in our 5G system. Further advancements in 5G security research are evident in studies focusing on specific threat vectors and vulnerabilities. The work in [26] is crucial in providing comprehensive datasets that encompass both IP-layer and Core Network attacks, facilitating the development of more effective security solutions. Concurrently, research works [7; 25] have highlighted critical vulnerabilities such as the susceptibility of 5G networks to DoS attacks and security header type attacks. Previously, refs. [28; 35; 36; 37] explored the automation test coverage to spot issues and potential security vulnerabilities in 4G and Long Term Evolution (LTE) networks. For instance, ref. [38] investigates the security aspects of control plane procedures based on dynamic testing of the control components in operational LTE networks. Aside from this, ref. [39] has explored the integration of AI with 5G technologies, and [13] explores technological advancements in intelligent cyber ranges, focusing on AI applications for improving cybersecurity training and experimentation. These studies highlight the integration of AI in creating dynamic and realistic cyber attack scenarios, enhancing the effectiveness of cybersecurity training. Similarly, the work of [27] has contributed to understanding dynamic network slicing, essential for accommodating diverse service demands. These studies lay the foundation for understanding the complex interplay between advanced network functionalities and security considerations in 5G network environments. The exploration of practical tools for testing and enhancing 5G network security has also been a focal point in recent research. The introduction of 5 Greplay [10] marks a significant step forward, providing a means to assess the resilience of 5G network components against diverse attack scenarios. It is an open-source 5G network traffic fuzzer designed to evaluate 5G components by replaying, modifying 5G network traffic, and injecting network scenarios into a target, which can be a 5G service such as Core Network (e.g., AMF, SMF) or a RAN network (e.g., gNodeB). This aligns with study [40] that explores the inherent weaknesses of 5G technology and underscores the pressing need for robust defense mechanisms. Such research is pivotal in developing comprehensive strategies to counteract emerging security threats in 5G networks. The work of [12; 14] demonstrates the use of a cyber range platform, SPIDER, for training cybersecurity professionals. Integrating machine learning-driven security analytics, this platform facilitates network traffic emulation and attacker connection detection. However, the implementation details of the 5G network environment are less transparent, probably due to its closed-source nature, which might limit the ability to reproduce or extend this training method in real-world cybersecurity scenarios. Incorporating these insights, it can be concluded that such reproducible training environments are crucial for enhancing the skills of defenders in identifying and mitigating cyberattacks in 5G networks.