Federated Network Intelligence Orchestration for Scalable and Automated FL-Based Anomaly Detection in B5G Networks
Source abstract
Abstract
The management of network intelligence in Beyond 5G (B5G) networks encompasses the complex challenges of scalability, dynamicity, interoperability, privacy, and security. These are essential steps towards achieving the realiz... | Find, read and cite all the research you need on Tech Science Press
Source: openalex_inverted_index · Quality: baseline
Research context
OpenAlex topics: Network Security and Intrusion Detection · Smart Grid Security and Resilience · Anomaly Detection Techniques and Applications
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
References (23)
Show source-provided references
1. Communication-efficient learning of deep networks from decentralized data
2. Survey of intrusion detection systems: Techniques, datasets and challenges10.1186/s42400-019-0038-7 ↗
3. Multi-stage optimized machine learning framework for network intrusion detection
4. A self-adaptive deep learning-based system for anomaly detection in 5G networks10.1109/ACCESS.2018.2803446 ↗
5. A. Thantharate, “FED6G: Federated chameleon learning for network slice management in beyond 5G systems,” presented at the Proc. 2022 IEEE 13th Ann. Inf. Technol. Electron. Mobile Commun. Conf. (IEMCON), Oct. 12–15, 2022, pp. 19–25. doi: 10.1109/IEMCON56893.2022.9946488.10.1109/IEMCON56893.2022.9946488 ↗
6. FedRelay: Federated relay learning for 6G mobile edge intelligence10.1109/TVT.2022.3225087 ↗
7. ZSM-based E2E security slice management for DDoS attack protection in MEC-enabled V2X environments
8. Security orchestration and enforcement in NFV/SDN-aware UAV deployments10.1109/ACCESS.2020.3010209 ↗
9. Evaluating FL for intrusion detection in Internet of Things: Review and challenges10.1016/j.comnet.2021.108661 ↗
10. Fed-ANIDS: FL for anomaly-based network intrusion detection systems10.1016/j.eswa.2023.121000 ↗
11. Federated machine learning: Survey, multi-level classification, desirable criteria and future directions in communication and networking systems10.1109/COMST.2021.3058573 ↗
12. Survey on federated learning enabling indoor navigation for industry 4.0 in B5G10.1016/j.future.2023.06.001 ↗
13. DRL-based joint resource allocation and device orchestration for hierarchical FL in NOMA-enabled industrial IoT10.1109/TII.2022.3170900 ↗
14. M. Camelo et al., “Requirements and specifications for the orchestration of network intelligence in 6G,” presented at the 2022 IEEE 19th Annu. Consum. Commun. Netw. Conf. (CCNC), Jan. 8–11, 2022, pp. 1–9. doi: 10.1109/CCNC49033.2022.9700729.10.1109/CCNC49033.2022.9700729 ↗
15. S. D’Oro, L. Bonati, M. Polese, and T. Melodia, “OrchestRAN: Network automation through orchestrated intelligence in the open RAN,” presented at the IEEE INFOCOM 2022—IEEE Conf. Comput. Commun., May 2–5, 2022, pp. 270–279. doi: 10.1109/INFOCOM48880.2022.9796744.10.1109/INFOCOM48880.2022.9796744 ↗
16. AI-based autonomous control, management, and orchestration in 5G: From standards to algorithms10.1109/MNET.001.2000047 ↗
17. Intrusion detection based on privacy-preserving FL for the industrial IoT10.1109/TII.2021.3126728 ↗
18. S. Samarakoon et al., “5G-NIDD: A comprehensive network intrusion detection dataset generated over 5G wireless network,” IEEE Dataport, 2022. doi: 10.21227/xtep-hv36.
19. A novel hybrid intrusion detection method integrating anomaly detection with misuse detection10.1016/j.eswa.2013.08.066 ↗
20. A novel time efficient learning-based approach for smart intrusion detection system10.1186/s40537-021-00498-8 ↗
21. Deep learning for cyber security intrusion detection: Approaches, datasets, and comparative study
22. S. I. Kim and H. S. Kim, “A VNF placement method based on VNF characteristics,” presented at the 2021 Int. Conf. Inf. Netw. (ICOIN), Jeju Island, Republic of Korea, Jan. 13–16, 2021, pp. 864–869. doi: 10.1109/ICOIN50884.2021.10.1109/ICOIN50884.2021.9334022 ↗
23. Capacitated shortest path tour problem-based integer linear programming for service chaining and function placement in NFV networks10.1109/TNSM.2020.3044329 ↗