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1. A 5G Standalone Network Analysis Testing and Security Vulnerability Detection using a Firecell Testbed

   https://doi.org/10.5121/csit.2024.141901  

   Anyakora, Ndidi; M_Akujuobi, Cajetan (October 2024, Academy & Industry Research Collaboration Center)

   With the proliferation of 5G networks, evaluating security vulnerabilities is crucial. This paper presents an implemented 5G standalone testbed operating in the mmWave frequency range for research and analysis. Over-the-air testing validates expected throughputs up to 5Gbps downlink and 1Gbps uplink, low latency, and robust connectivity. Detailed examination of captured network traffic provides insights into protocol distribution and signalling flows. The comparative evaluation shows only 0.45% packet loss on the testbed versus 2.7% in prior simulations, proving improved reliability. Thetestbed achieved a throughput of up to 5Gbps downlink and 1Gbps uplink with minimal latency, meeting expected 5G network benchmarks. The results highlight the efficacy of the testbed for security assessments, performance benchmarking, and progression towards 6G systems. This paper demonstrates a robust platform to facilitate innovation in 5G and beyond through practical experimentation. 

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2. Testbeds and Evaluation Frameworks for Anomaly Detection within Built Environments: A Systematic Review

   https://doi.org/10.1145/3722213  

   Alosaimi, Mohammed; Rana, Omer; Perera, Charith (September 2025, ACM Computing Surveys)

   The Internet of Things (IoT) has revolutionized built environments by enabling seamless data exchange among devices such as sensors, actuators, and computers. However, IoT devices often lack robust security mechanisms, making them vulnerable to cyberattacks, privacy breaches, and operational anomalies caused by environmental factors or device faults. While anomaly detection techniques are critical for securing IoT systems, the role of testbeds in evaluating these techniques has been largely overlooked. This systematic review addresses this gap by treating testbeds as first-class entities essential for the standardized evaluation and validation of anomaly detection methods in built environments. We analyze testbed characteristics, including infrastructure configurations, device selection, user-interaction models, and methods for anomaly generation. We also examine evaluation frameworks, highlighting key metrics and integrating emerging technologies such as edge computing and 5G networks into testbed design. By providing a structured and comprehensive approach to testbed development and evaluation, this paper offers valuable guidance to researchers and practitioners in enhancing the reliability and effectiveness of anomaly detection systems. Our findings contribute to the development of more secure, adaptable, and scalable IoT systems, ultimately improving the security, resilience, and efficiency of built environments. 

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3. VET5G: A Virtual End-to-End Testbed for 5G Network Security Experimentation

   https://doi.org/10.1145/3546096.3546111  

   Wen, Zhixin; Pacherkar, Harsh Sanjay; Yan, Guanhua (August 2022, The 15th Workshop on Cyber Security Experimentation and Test)

   As 5G networks are gradually rolled out worldwide, it is important to ensure that their network infrastructures are resilient against malicious attacks. This work presents VET5G, a new virtual end-to-end testbed for 5G network security research experiments or training activities such as Capture-The-Flag competitions. The distinguishing features of VET5G include a home-grown 5G core network emulator written in Rust to ensure memory and thread safety, integration of OpenAirInterface’s Radio Access Network emulator and the official Android emulator to achieve full end-to-end 5G network emulation, inclusion of a reference P4 software switch to assist with prototyping of defense mechanisms for 5G data planes, implementation of Python APIs for easy 5G network experimentation, and adoption of JupyterHub to support multi-user experimentation. In our experiments we demonstrate how to use VET5G for two attack scenarios in 5G networks as well as its performance when it is used in a 5G hacking project for a Mobile Systems Security course. 

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4. Enhanced Real-Time Threat Detection in 5G Networks: A Self-Attention RNN Autoencoder Approach for Spectral Intrusion Analysis

   Kouchaki, Mohammadreza; Zhang, Minglong; Abdalla, Aly S; Lan, Guangchen; Brinton, Christopher G; Marojevic, Vuk (December 2024, 2024 22nd International Symposium on Modeling and Optimization in Mobile, Ad Hoc, and Wireless Networks (WiOpt))

   In the rapidly evolving landscape of 5G technology, safeguarding Radio Frequency (RF) environments against sophisticated intrusions is paramount, especially in dynamic spectrum access and management. This paper presents an enhanced experimental model that integrates a self-attention mechanism with a Recurrent Neural Network (RNN)-based autoencoder for the detection of anomalous spectral activities in 5G networks at the waveform level. Our approach, grounded in time-series analysis, processes in-phase and quadrature (I/Q) samples to identify irregularities that could indicate potential jamming attacks. The model's architecture, augmented with a self-attention layer, extends the capabilities of RNN autoen-coders, enabling a more nuanced understanding of temporal dependencies and contextual relationships within the RF spectrum. Utilizing a simulated 5G Radio Access Network (RAN) test-bed constructed with srsRAN 5G and Software Defined Radios (SDRs), we generated a comprehensive stream of data that reflects real-world RF spectrum conditions and attack scenarios. The model is trained to reconstruct standard signal behavior, establishing a normative baseline against which deviations, indicative of security threats, are identified. The proposed architecture is designed to balance between detection precision and computational efficiency, so the LSTM network, enriched with self-attention, continues to optimize for minimal execution latency and power consumption. Conducted on a real-world SDR-based testbed, our results demonstrate the model's improved performance and accuracy in threat detection. 

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5. Triton: A Software-Reconfigurable Federated Avionics Testbed

   Crow, Sam; Farinholt, Brown; Johannesmeyer, Brian; Koscher, Karl; Checkoway, Stephen; Savage, Stefan; Schulman, Aaron; Snoeren, Alex C; Levchenko, Kirill (August 2019, USENIX Workshop on Cyber Security Experimentation and Test (CSET))

   This paper describes the Triton federated-avionics security testbed that supports testing real aircraft electronic systems for security vulnerabilities. Because modern aircraft are complex systems of systems, the Triton testbed allows multiple systems to be instantiated for analysis in order to observe the aggregate behavior of multiple aircraft systems and identify their potential impact on flight safety. We describe two attack scenarios that motivated the design of the Triton testbed: ACARS message spoofing and the software update process for aircraft systems. The testbed allows us to analyze both scenarios to determine whether adversarial interference in their expected operation could cause harm. This paper does not describe any vulnerabilities in real aircraft systems; instead, it describes the design of the Triton testbed and our experiences using it. One of the key features of the Triton testbed is the ability to mix simulated, emulated, and physical electronic systems as necessary for a particular experiment or analysis task. A physical system may interact with a simulated component or a system whose software is running in an emulator. To facilitate rapid reconfigurability, Triton is also entirely software reconfigurable: all wiring between components is virtual and can be changed without physical access to components. A prototype of the Triton testbed is used at two universities to evaluate the security of aircraft systems. 

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