With the emerging applications of the Internet of things,artificial intelligence,and satellite communications,the future network will be featured as the Internet of everything around the globe.The network heterogeneit...With the emerging applications of the Internet of things,artificial intelligence,and satellite communications,the future network will be featured as the Internet of everything around the globe.The network heterogeneity,applications cloudification,and personalized user services demand a revolutionary change in the network architecture.With the rapid development of cloud native technology,the new network should support heterogeneous networks and personalized quality of services for users.In this paper,we propose a Cybertwinbased cloud native network(CCNN)that merges the radio access network(RAN),the IP bearer network,and the data center network and is based on the cloud native data center network using Kubernetes as a network operating system for unified virtualization of computing,storage,and network resources,unified scheduling and allocation,and unified operation and management.Then,we propose a fully decoupled RAN architecture that can flexibly and efficiently utilize the resource for personlized user services.We also propose a Cybertwin-based management framework built on Kubernetes for integrated networking,computing and storage resource scheduling.Finally,we design an immunology-inspired intrinsic security architecture with zero trust security system and adaptive defense system.The proposed CCNN is a new network architecture expected to address future generation communications and networks challenges.展开更多
Roaming in 5G networks enables seamless global mobility but also introduces significant security risks due to legacy protocol dependencies,uneven Security Edge Protection Proxy(SEPP)deployment,and the dynamic nature o...Roaming in 5G networks enables seamless global mobility but also introduces significant security risks due to legacy protocol dependencies,uneven Security Edge Protection Proxy(SEPP)deployment,and the dynamic nature of inter-Public Land Mobile Network(inter-PLMN)signaling.Traditional rule-based defenses are inadequate for protecting cloud-native 5G core networks,particularly as roaming expands into enterprise and Internet of Things(IoT)domains.This work addresses these challenges by designing a scalable 5G Standalone testbed,generating the first intrusion detection dataset specifically tailored to roaming threats,and proposing a deep learning based intrusion detection framework for cloud-native environments.Six deep learning models including Multilayer Perceptron(MLP),one-dimensional Convolutional Neural Network(1D CNN),Autoencoder(AE),Recurrent Neural Network(RNN),Gated Recurrent Unit(GRU),and Long Short-Term Memory(LSTM)were evaluated on the dataset using both weighted and balanced metrics to account for strong class imbalance.While all models achieved over 99%accuracy,recurrent architectures such as GRU and LSTM outperformed others in balanced accuracy and macro-level evaluation,demonstrating superior effectiveness in detecting rare but high-impact attacks.These results confirm the importance of sequence-aware Artificial Intelligence(AI)models for securing roaming scenarios,where transient and contextdependent threats are common.The proposed framework provides a foundation for intelligent,adaptive intrusion detection in 5G and offers a path toward resilient security in Beyond 5G and 6G networks.展开更多
As an emerging technology,digital twin is expected to bring novel application modes to the whole life cycle process of unmanned ground equipment,including research and development,design,control optimization,operation...As an emerging technology,digital twin is expected to bring novel application modes to the whole life cycle process of unmanned ground equipment,including research and development,design,control optimization,operation and maintenance,etc.The highly dynamic,complex,and uncertain characteristics of unmanned ground equipment and the battlefield environment also pose new challenges for digital twin technology.Starting from the new challenges faced by the digital twin of unmanned ground equipment,this paper designs a service-oriented cloud-edge-end collaborative platform architecture of the digital twin system of unmanned ground equipment,and further analyzes several key technologies supporting the implementation of the platform architecture.展开更多
基金supported in part by the Key Area Research and Development Program of Guangdong Province under Grant 2020B0101110003in part by the major key project of Peng Cheng Laboratory and the Basic and Frontier Research Project of PCL.The associate editor coordinating the review of this paper and approving it for publication was L.Bai.
文摘With the emerging applications of the Internet of things,artificial intelligence,and satellite communications,the future network will be featured as the Internet of everything around the globe.The network heterogeneity,applications cloudification,and personalized user services demand a revolutionary change in the network architecture.With the rapid development of cloud native technology,the new network should support heterogeneous networks and personalized quality of services for users.In this paper,we propose a Cybertwinbased cloud native network(CCNN)that merges the radio access network(RAN),the IP bearer network,and the data center network and is based on the cloud native data center network using Kubernetes as a network operating system for unified virtualization of computing,storage,and network resources,unified scheduling and allocation,and unified operation and management.Then,we propose a fully decoupled RAN architecture that can flexibly and efficiently utilize the resource for personlized user services.We also propose a Cybertwin-based management framework built on Kubernetes for integrated networking,computing and storage resource scheduling.Finally,we design an immunology-inspired intrinsic security architecture with zero trust security system and adaptive defense system.The proposed CCNN is a new network architecture expected to address future generation communications and networks challenges.
基金supported by Institute of Information&communications Technology Planning&Evaluation(IITP)grant funded by the Korea government(MSIT)(RS-2024-00441484,Development of Open Roaming Technology for Private 5G Network)。
文摘Roaming in 5G networks enables seamless global mobility but also introduces significant security risks due to legacy protocol dependencies,uneven Security Edge Protection Proxy(SEPP)deployment,and the dynamic nature of inter-Public Land Mobile Network(inter-PLMN)signaling.Traditional rule-based defenses are inadequate for protecting cloud-native 5G core networks,particularly as roaming expands into enterprise and Internet of Things(IoT)domains.This work addresses these challenges by designing a scalable 5G Standalone testbed,generating the first intrusion detection dataset specifically tailored to roaming threats,and proposing a deep learning based intrusion detection framework for cloud-native environments.Six deep learning models including Multilayer Perceptron(MLP),one-dimensional Convolutional Neural Network(1D CNN),Autoencoder(AE),Recurrent Neural Network(RNN),Gated Recurrent Unit(GRU),and Long Short-Term Memory(LSTM)were evaluated on the dataset using both weighted and balanced metrics to account for strong class imbalance.While all models achieved over 99%accuracy,recurrent architectures such as GRU and LSTM outperformed others in balanced accuracy and macro-level evaluation,demonstrating superior effectiveness in detecting rare but high-impact attacks.These results confirm the importance of sequence-aware Artificial Intelligence(AI)models for securing roaming scenarios,where transient and contextdependent threats are common.The proposed framework provides a foundation for intelligent,adaptive intrusion detection in 5G and offers a path toward resilient security in Beyond 5G and 6G networks.
文摘As an emerging technology,digital twin is expected to bring novel application modes to the whole life cycle process of unmanned ground equipment,including research and development,design,control optimization,operation and maintenance,etc.The highly dynamic,complex,and uncertain characteristics of unmanned ground equipment and the battlefield environment also pose new challenges for digital twin technology.Starting from the new challenges faced by the digital twin of unmanned ground equipment,this paper designs a service-oriented cloud-edge-end collaborative platform architecture of the digital twin system of unmanned ground equipment,and further analyzes several key technologies supporting the implementation of the platform architecture.
