Federated Network Intelligence Orchestration for Scalable and Automated FL-Based Anomaly Detection in B5G Networks  

作　　者：Pablo Fernández Saura José M.Bernabé Murcia Emilio García de la Calera Molina Alejandro Molina Zarca Jorge Bernal Bernabé Antonio F.Skarmeta Gómez 

机构地区：[1]Department of Information and Communications Engineering,University of Murcia,Murcia,30100,Spain [2]University Center of Defense,Spanish Air Force Academy,San Javier,30720,Spain

出　　处：《Computers, Materials & Continua》2024年第7期163-193,共31页计算机、材料和连续体（英文）

基　　金：supported by the grants:PID2020-112675RBC44(ONOFRE-3),funded by MCIN/AEI/10.13039/501100011033;Horizon Project RIGOUROUS funded by European Commission,GA:101095933;TSI-063000-2021-{36,44,45,62}(Cerberus)funded by MAETD’s 2021 UNICO I+D Program.

摘　　要：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 realization of truly ubiquitous Artificial Intelligence(AI)-based analytics,empowering seamless integration across the entire Continuum(Edge,Fog,Core,Cloud).This paper introduces a Federated Network Intelligence Orchestration approach aimed at scalable and automated Federated Learning(FL)-based anomaly detection in B5Gnetworks.By leveraging a horizontal Federated learning approach based on the FedAvg aggregation algorithm,which employs a deep autoencoder model trained on non-anomalous traffic samples to recognize normal behavior,the systemorchestrates network intelligence to detect and prevent cyber-attacks.Integrated into a B5G Zero-touch Service Management(ZSM)aligned Security Framework,the proposal utilizes multi-domain and multi-tenant orchestration to automate and scale the deployment of FL-agents and AI-based anomaly detectors,enhancing reaction capabilities against cyber-attacks.The proposed FL architecture can be dynamically deployed across the B5G Continuum,utilizing a hierarchy of Network Intelligence orchestrators for real-time anomaly and security threat handling.Implementation includes FL enforcement operations for interoperability and extensibility,enabling dynamic deployment,configuration,and reconfiguration on demand.Performance validation of the proposed solution was conducted through dynamic orchestration,FL,and real-time anomaly detection processes using a practical test environment.Analysis of key performance metrics,leveraging the 5G-NIDD dataset,demonstrates the system’s capability for automatic and near real-time handling of anomalies and attacks,including real-time network monitoring and countermeasure implementation for mitigation.

关 键 词：Federated learning 6G ORCHESTRATION anomaly detection security policy 

分 类 号：TN929.5[电子电信—通信与信息系统]