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: "securing physical layer communications for cognitive radio networks"
  Abstract: This article investigates the physical-layer security of CR networks, which are vulnerable to various newly arising attacks targeting the weaknesses of CR communications and networking. We first review a range of physical-layer attacks in CR networks, including primary user emulation, sensing falsification, intelligence compromise, jamming, and eavesdropping attacks. Then we focus on the physical-layer security of CR networks against eavesdropping and examine the secrecy performance of cognitive communications in terms of secrecy outage probability. We further consider the use of relays for improving CR security against eavesdropping and propose an opportunistic relaying scheme, where a relay node that makes CR communications most resistant to eavesdropping is chosen to participate in assisting the transmission from a cognitive source to its destination. It is illustrated that the physical- layer secrecy of CR communications relying on opportunistic relaying can be significantly improved by increasing the number of relays, showing the security benefit of exploiting relay nodes. Finally, we present some open challenges in the field of relay-assisted physical-layer security for CR networks.

Connected through hyperedge HE-1 (induced by source paper "adversarial deep learning for over the air spectrum poisoning attacks"):
  with members:
    - "adversarial examples in rf deep learning detection of the attack and its physical robustness"
    - "spectrum data poisoning with adversarial deep learning"
    - "communication without interception defense against deep learning based modulation detection"
    - "adversarial attacks and defences competition"
    - "active deep learning attacks under strict rate limitations for online api calls"
    - "deep learning for signal authentication and security in massive internet of things systems"
    - "generative adversarial learning for spectrum sensing"
    - "deep learning for launching and mitigating wireless jamming attacks"

Connected through hyperedge HE-2 (induced by source paper "secrecy outage analysis of non orthogonal spectrum sharing for heterogeneous cellular networks"):
  with members:
    - "security reliability tradeoff for distributed antenna systems in heterogeneous cellular networks"
    - "intelligent interference exploitation for heterogeneous cellular networks against eavesdropping"
    - "power domain non orthogonal multiple access noma in 5g systems potentials and challenges"
    - "a new look at physical layer security caching and wireless energy harvesting for heterogeneous ultra dense networks"
    - "physical layer security for spectrum sharing systems"
    - "artificial noise aided secure transmission in large scale spectrum sharing networks"
    - "location based beamforming and physical layer security in rician wiretap channels"
    - "physical layer security in millimeter wave cellular networks"

Connected through hyperedge HE-3 (induced by source paper "spectrum data poisoning with adversarial deep learning"):
  with members:
    - "generative adversarial learning for spectrum sensing"
    - "deep learning for launching and mitigating wireless jamming attacks"
    - "convolutional radio modulation recognition networks"
    - "stealing machine learning models via prediction apis"
    - "adversarial examples in the physical world"
    - "evasion attacks against machine learning at test time"
    - "poisoning attacks against support vector machines"

Connected through hyperedge HE-4 (induced by source paper "deep learning for launching and mitigating wireless jamming attacks"):
  with members:
    - "generative adversarial networks for black box api attacks with limited training data"
    - "spectrum data poisoning with adversarial deep learning"
    - "active deep learning attacks under strict rate limitations for online api calls"
    - "generative adversarial learning for spectrum sensing"
    - "artificial neural networks based machine learning for wireless networks a tutorial"
    - "deep sensing cooperative spectrum sensing based on convolutional neural networks"
    - "power of deep learning for channel estimation and signal detection in ofdm systems"
    - "learning from simulated and unsupervised images through adversarial training"

Connected through hyperedge HE-5 (induced by source paper "recent advances in cloud radio access networks system architectures key techniques and open issues"):
  with members:
    - "fronthaul compression and precoding design for c rans over ergodic fading channels"
    - "optimal fronthaul quantization for cloud radio positioning"
    - "inter tier interference suppression in heterogeneous cloud radio access networks"
    - "contract based interference coordination in heterogeneous cloud radio access networks"
    - "are heterogeneous cloud based radio access networks cost effective"
    - "energy efficient resource assignment and power allocation in heterogeneous cloud radio access networks"
    - "cooperative interference mitigation and handover management for heterogeneous cloud small cell networks"
    - "fronthaul constrained cloud radio access networks insights and challenges"

Connected through hyperedge HE-6 (induced by source paper "a survey on wireless security technical challenges recent advances and future trends"):
  with members:
    - "relay selection for wireless communications against eavesdropping a security reliability trade off perspective"
    - "improving physical layer security in wireless communications using diversity techniques"
    - "secrecy outage and diversity analysis of cognitive radio systems"
    - "security versus reliability analysis of opportunistic relaying"
    - "what will 5g be"
    - "intercept probability analysis of cooperative wireless networks with best relay selection in the presence of eavesdropping attack"
    - "optimal relay selection for physical layer security in cooperative wireless networks"
    - "physical layer security with multiuser scheduling in cognitive radio networks"

Connected through hyperedge HE-7 (induced by source paper "robust layered transmission in secure miso multiuser unicast cognitive radio systems"):
  with members:
    - "robust beamforming for secure communication in systems with wireless information and power transfer"
    - "secrecy outage and diversity analysis of cognitive radio systems"
    - "secure and green swipt in distributed antenna networks with limited backhaul capacity"
    - "radio resource allocation for scalable video services over wireless cellular networks"
    - "power efficient miso beamforming for secure layered transmission"
    - "secrecy wireless information and power transfer with miso beamforming"
    - "spatially selective artificial noise aided transmit optimization for miso multi eves secrecy rate maximization"
    - "distributed robust multicell coordinated beamforming with imperfect csi an admm approach"

Connected through hyperedge HE-8 (induced by source paper "relay selection for wireless communications against eavesdropping a security reliability trade off perspective"):
  with members:
    - "improving physical layer security in wireless communications using diversity techniques"
    - "security versus reliability analysis of opportunistic relaying"
    - "semantically secure lattice codes for the gaussian wiretap channel"
    - "optimal relay selection for physical layer security in cooperative wireless networks"
    - "robust beamforming for security in mimo wiretap channels with imperfect csi"
    - "on the throughput of secure hybrid arq protocols for gaussian block fading 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.IT(Information Theory)