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: "using the physical layer for wireless authentication in time variant channels"
  Abstract: The wireless medium contains domain-specific information that can be used to complement and enhance traditional security mechanisms. In this paper we propose ways to exploit the spatial variability of the radio channel response in a rich scattering environment, as is typical of indoor environments. Specifically, we describe a physical-layer authentication algorithm that utilizes channel probing and hypothesis testing to determine whether current and prior communication attempts are made by the same transmit terminal. In this way, legitimate users can be reliably authenticated and false users can be reliably detected. We analyze the ability of a receiver to discriminate between transmitters (users) according to their channel frequency responses. This work is based on a generalized channel response with both spatial and temporal variability, and considers correlations among the time, frequency and spatial domains. Simulation results, using the ray-tracing tool WiSE to generate the time-averaged response, verify the efficacy of the approach under realistic channel conditions, as well as its capability to work under unknown channel variations.

Connected through hyperedge HE-1 (induced by source paper "on the effective capacity of an underwater acoustic channel under impersonation attack"):
  with members:
    - "impersonation detection in line of sight underwater acoustic sensor networks"
    - "physical layer authentication in mission critical mtc networks a security and delay performance analysis"
    - "channel impulse response based distributed physical layer authentication"
    - "energy efficiency optimization for mimo ofdm mobile multimedia communication systems with qos constraints"
    - "effective capacity of delay constrained cognitive radio links exploiting primary feedback"
    - "effective capacity of two hop wireless communication systems"
    - "effective capacity analysis of cognitive radio channels for quality of service provisioning"

Connected through hyperedge HE-2 (induced by source paper "performance of statistical and machine learning techniques for physical layer authentication"):
  with members:
    - "machine learning for intelligent authentication in 5g and beyond wireless networks"
    - "statistical and machine learning based decision techniques for physical layer authentication"
    - "learning aided physical layer authentication as an intelligent process"
    - "application of machine learning for channel based message authentication in mission critical machine type communication"
    - "analysis of channel based user authentication by key less and key based approaches"
    - "physical layer security in heterogeneous cellular networks"

Connected through hyperedge HE-3 (induced by source paper "secret key authentication capacity region part i average authentication rate"):
  with members:
    - "inner bound for the capacity region of noisy channels with an authentication requirement"
    - "keyless authentication in the presence of a simultaneously transmitting adversary"
    - "on the optimality of keyless authentication in a noisy model"

Connected through hyperedge HE-4 (induced by source paper "secret key authentication capacity region part ii typical authentication rate"):
  with members:
    - "keyless authentication in the presence of a simultaneously transmitting adversary"
    - "on the optimality of keyless authentication in a noisy model"

Connected through hyperedge HE-5 (induced by source paper "private authentication optimal information theoretic schemes"):
  with members:
    - "controllable identifier measurements for private authentication with secret keys"
    - "the capacity of private information retrieval"
    - "utility privacy tradeoffs in databases an information theoretic approach"
    - "vespa vehicular security and privacy preserving architecture"

Connected through hyperedge HE-6 (induced by source paper "a light weight authentication scheme for air force internet of things"):
  with members:
    - "internet of things security and forensics challenges and opportunities"
    - "usbee air gap covert channel via electromagnetic emission from usb"
    - "device fingerprinting in wireless networks challenges and opportunities"
    - "internet of things iot a vision architectural elements and future directions"

Connected through hyperedge HE-7 (induced by source paper "statistical and machine learning based decision techniques for physical layer authentication"):
  with members:
    - "learning aided physical layer authentication as an intelligent process"
    - "application of machine learning for channel based message authentication in mission critical machine type communication"
    - "analysis of channel based user authentication by key less and key based approaches"

Connected through hyperedge HE-8 (induced by source paper "physical layer authentication in mission critical mtc networks a security and delay performance analysis"):
  with members:
    - "application of machine learning for channel based message authentication in mission critical machine type communication"
    - "channel impulse response based distributed physical layer authentication"
    - "physical layer authentication for mission critical machine type communication using gaussian mixture model based clustering"
    - "secure transmission of delay sensitive data over wireless fading channels"
    - "fingerprints in the ether using the physical layer for wireless authentication"

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.CR(Cryptography and Security)