Zujany Salazar
Huu Nghia Nguyen
ABSTRACT
The fifth generation of mobile broadband is more than just an evolution to provide more mobile bandwidth, massive machine-type communications, and ultra-reliable and low-latency communications. It relies on a complex, dynamic and heterogeneous environment that implies addressing numerous testing and security challenges. In this paper we present 5Greplay, an open-source 5G network traffic fuzzer that enables the evaluation of 5G components by replaying and modifying 5G network traffic by creating and injecting network scenarios into a target that can be a 5G core service (e.g., AMF, SMF) or a RAN network (e.g., gNodeB). The tool provides the ability to alter network packets online or offline in both control and data planes in a very flexible manner. The experimental evaluation conducted against open-source based 5G platforms, showed that the target services accept traffic being altered by the tool, and that it can reach up to 9.56 Gbps using only 1 processor core to replay 5G traffic.
- The 3rd Generation Partnership Project (3GPP). 2020. 3GPP TS 33.117 – Catalogue of general security assurance requirements. https://itectec.com/archive/3gpp-specification-ts-33-117/Google Scholar
- The 3rd Generation Partnership Project (3GPP). 2021. 3GPP TS 33.512 – 5G Security Assurance Specification (SCAS); Access and Mobility management Function (AMF). https://itectec.com/archive/3gpp-specification-ts-33-512/Google Scholar
- Ijaz Ahmad, Tanesh Kumar, Madhusanka Liyanage, Jude Okwuibe, Mika Ylianttila, and Andrei Gurtov. 2018. Overview of 5G Security Challenges and Solutions. IEEE Communications Standards Magazine 2, 1 (2018), 36–43. https://doi.org/10.1109/MCOMSTD.2018.1700063Google ScholarCross Ref
- David Basin, Jannik Dreier, Lucca Hirschi, Saša Radomirovic, Ralf Sasse, and Vincent Stettler. 2018. A Formal Analysis of 5G Authentication. In Proceedings of the 2018 ACM SIGSAC Conference on Computer and Communications Security (Toronto, Canada) (CCS ’18). Association for Computing Machinery, New York, NY, USA, 1383–1396. https://doi.org/10.1145/3243734.3243846Google ScholarDigital Library
- ENISA. 2021. ENISA threat landscape for 5G Networks. https://www.enisa.europa.eu/publications/enisa-threat-landscape-for-5g-networksGoogle Scholar
- Ericsson. 2018. A guide to 5G network security. Conceptualizing security in mobile communication networks – how does 5G fit in?https://www.ericsson.com/en/security/a-guide-to-5g-network-securityGoogle Scholar
- ETSI. 2017. ETSI GS NFV-SEC 013. https://www.etsi.org/deliver/etsi_gs/NFV-SEC/001_099/013/03.01.01_60/gs_NFV-SEC013v030101p.pdfGoogle Scholar
- ETSI. 2018. ETSI TS 138 412. https://www.etsi.org/deliver/etsi_ts/138400_138499/138412/15.00.00_60/ts_138412v150000p.pdfGoogle Scholar
- ETSI. 2020. ETSI TS 133 512. https://www.etsi.org/deliver/etsi_ts/133500_133599/133512/16.03.00_60/ts_133512v160300p.pdfGoogle Scholar
- Marco Antonio Sotelo Monge, Andrés Herranz González, Borja Lorenzo Fernández, Diego Maestre Vidal, Guillermo Rius García, and Jorge Maestre Vidal. 2019. Traffic-flow analysis for source-side DDoS recognition on 5G environments. Journal of Network and Computer Applications 136 (2019), 114–131. https://doi.org/10.1016/j.jnca.2019.02.030Google ScholarDigital Library
- Hajar Moudoud, Lyes Khoukhi, and Soumaya Cherkaoui. 2021. Prediction and Detection of FDIA and DDoS Attacks in 5G Enabled IoT. IEEE Network 35, 2 (2021), 194–201. https://doi.org/10.1109/mnet.011.2000449Google ScholarCross Ref
- Markus Ring, Daniel Schlör, Dieter Landes, and Andreas Hotho. 2019. Flow-based network traffic generation using Generative Adversarial Networks. Computers & Security 82(2019), 156–172. https://doi.org/10.1016/j.cose.2018.12.012Google ScholarDigital Library
- Positive Technologies. 2021. 5g Standalone Core Security Research. https://positive-tech.com/storage/articles/5g-sa-core-security-research/5g-sa-core-security-research.pdfGoogle Scholar
- Silvio Valenti, Dario Rossi, Alberto Dainotti, Antonio Pescapè, Alessandro Finamore, and Marco Mellia. 2013. Reviewing Traffic Classification. Springer Berlin Heidelberg, Berlin, Heidelberg, 123–147. https://doi.org/10.1007/978-3-642-36784-7_6Google Scholar
- W.Eric Wong and Aditya P. Mathur. 1995. Reducing the cost of mutation testing: An empirical study. Journal of Systems and Software 31, 3 (1995), 185–196. https://doi.org/10.1016/0164-1212(94)00098-0Google ScholarDigital Library
Recommendations
HTTP/2 Attacks Generation using 5Greplay
ARES '23: Proceedings of the 18th International Conference on Availability, Reliability and Security5G networks become increasingly pervasive, ensuring the robustness and integrity of network functions. The adoption of HTTP/2 in 5G core functions brings notable performance benefits but also introduces potential security risks. By analyzing HTTP/2 ...
A model-based attack injection approach for security validation
SIN '11: Proceedings of the 4th international conference on Security of information and networksCommunication systems are inherently buggy. These flaws can lead to security breaches in applications, which a malicious user could exploit to cause security failures in the system and, under certain circumstances, to take complete control of the ...
Invited A new traffic engineering manager for DiffServ/MPLS networks: design and implementation on an IP QoS Testbed
In a multi-service network, different applications have varying QoS requirements. The IETF has proposed the DiffServ architecture as a scalable solution to provide Quality of Service (QoS) in IP Networks. In order to provide quantitative guarantees and ...
Comments