human: Given a node-centered hypergraph: <hypergraph>, where nodes represent papers and hyperedges represent sets of papers co-cited by a source paper.

Details of the hypergraph:
Center node: "providing physical layer security for mission critical machine type communication"
  Abstract: The design of wireless systems for Mission Critical Machine Type Communication (MC-MTC) is currently a hot research topic. Wireless systems are considered to provide numerous advantages over wired systems in industrial applications for example. However, due to the broadcast nature of the wireless channel, such systems are prone to a wide range of cyber attacks. These range from passive eavesdropping attacks to active attacks like data manipulation or masquerade attacks. Therefore it is necessary to provide reliable and efficient security mechanisms. One of the most important security issue in such a system is to ensure integrity as well as authenticity of exchanged messages over the air between communicating devices in order to prohibit active attacks. In the present work, an approach on how to achieve this goal in MC-MTC systems based on Physical Layer Security (PHYSEC), especially a new method based on keeping track of channel variations, will be presented and a proof-of-concept evaluation is given.

Connected through hyperedge HE-1 (induced by source paper "application of machine learning for channel based message authentication in mission critical machine type communication"):
  with members:
    - "fingerprints in the ether using the physical layer for wireless authentication"
    - "using the physical layer for wireless authentication in time variant channels"

Connected through hyperedge HE-2 (induced by source paper "physical layer authentication for mission critical machine type communication using gaussian mixture model based clustering"):
  with members:
    - "fingerprints in the ether using the physical layer for wireless authentication"
    - "using the physical layer for wireless authentication in time variant channels"

Question: Please tell me which class the center node 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)