human: Given a hyperedge-centered hypergraph: <hypergraph>, where the center hyperedge is induced by one source paper and its member nodes are the cited papers.

Details of the hypergraph:
Center hyperedge (induced by source paper "guidelines for 5g end to end architecture and security issues"):
  Abstract: Hackers target their attacks on the most vulnerable parts of a system. A system is therefore only as strong as its weakest part, similar to the Cannikin Law, which states that the capacity of a barrel of water depends on the height of the shortest rather than the longest piece of wood. To ensure the security of 5G networks, we first need to understand the overall 5G architecture and examine the potential threats instead of merely setting up a firewall. However, 5G networks will have tremendous coverage. The development of 5G techniques require extensive resources, leading to intense competition between countries attempting to develop 5G networks. Many outstanding papers discuss the techniques for developing specific aspects of the 5G architecture, but to the best of our knowledge, few provide an overview of a complete 5G network. This presents us with a difficult situation because we need to consider the overall architecture to ensure the security of 5G networks. To address that problem, in this paper we provide essential guidelines for understanding the architecture of 5G. We introduce 5G scenarios, outline the network architecture, and highlight the potential security issues for the various components of a 5G network. This paper is intended to facilitate a preliminary understanding of the 5G architecture and the possible security concerns of the various components. The end to end (E2E) 5G network architecture is composed of a next-generation radio access network (NG-RAN), multi-access edge computing (MEC), virtual evolved packet core (vEPC), a data network (DN) and a cloud service. Network slicing (NS), network function virtualization (NFV), NFV Management and Orchestration (MANO) and software-defined networking (SDN) are also important techniques for achieving 5G network architectures.

Includes members:
  Member "deep learning for malicious flow detection":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "recover and identify a generative dual model for cross resolution person re identification")
  Member "nfv and sdn key technology enablers for 5g networks":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "5g network slicing using sdn and nfv a survey of taxonomy architectures and future challenges")

Question: Please tell me which class the source paper belongs to. The 40 classes are: cs.NA(Numerical Analysis), cs.MM(Multimedia), cs.LO(Logic in Computer Science), cs.CY(Computers and Society), cs.CR(Cryptography and Security), cs.DC(Distributed, Parallel, and Cluster Computing), cs.HC(Human-Computer Interaction), cs.CE(Computational Engineering, Finance, and Science), cs.NI(Networking and Internet Architecture), cs.CC(Computational Complexity), cs.AI(Artificial Intelligence), cs.MA(Multiagent Systems), cs.GL(General Literature), cs.NE(Neural and Evolutionary Computing), cs.SC(Symbolic Computation), cs.AR(Hardware Architecture), cs.CV(Computer Vision and Pattern Recognition), cs.GR(Graphics), cs.ET(Emerging Technologies), cs.SY(Systems and Control), cs.CG(Computational Geometry), cs.OH(Other Computer Science), cs.PL(Programming Languages), cs.SE(Software Engineering), cs.LG(Machine Learning), cs.SD(Sound), cs.SI(Social and Information Networks), cs.RO(Robotics), cs.IT(Information Theory), cs.PF(Performance), cs.CL(Computation and Language), cs.IR(Information Retrieval), cs.MS(Mathematical Software), cs.FL(Formal Languages and Automata Theory), cs.DS(Data Structures and Algorithms), cs.OS(Operating Systems), cs.GT(Computer Science and Game Theory), cs.DB(Databases), cs.DL(Digital Libraries), cs.DM(Discrete Mathematics). Directly output the class name.

gpt: cs.NI(Networking and Internet Architecture)