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: "detecting sybil attacks using proofs of work and location in vanets"
  Abstract: In this paper, we propose a Sybil attack detection scheme using proofs of work and location. The idea is that each road side unit (RSU) issues a signed time-stamped tag as a proof for the vehicle's anonymous location. Proofs sent from multiple consecutive RSUs is used to create vehicle trajectory which is used as vehicle anonymous identity. Also, one RSU is not able to issue trajectories for vehicles, rather the contributions of several RSUs are needed. By this way, attackers need to compromise an infeasible number of RSUs to create fake trajectories. Moreover, upon receiving the proof of location from an RSU, the vehicle should solve a computational puzzle by running proof of work (PoW) algorithm. So, it should provide a valid solution (proof of work) to the next RSU before it can obtain a proof of location. Using the PoW can prevent the vehicles from creating multiple trajectories in case of low-dense RSUs. Then, during any reported event, e.g., road congestion, the event manager uses a matching technique to identify the trajectories sent from Sybil vehicles. The scheme depends on the fact that the Sybil trajectories are bounded physically to one vehicle; therefore, their trajectories should overlap. Extensive experiments and simulations demonstrate that our scheme achieves high detection rate to Sybil attacks with low false negative and acceptable communication and computation overhead.

Connected through hyperedge HE-1 (induced by source paper "performance analysis of mobile cellular connected drones under practical antenna configurations"):
  with members:
    - "optimizing joint probabilistic caching and channel access for clustered d2d networks"
    - "3gpp inspired stochastic geometry based mobility model for a drone cellular network"
    - "privacy preserving smart parking system using blockchain and private information retrieval"
    - "b ride ride sharing with privacy preservation trust and fair payment atop public blockchain"
    - "on the reliability of wireless virtual reality at terahertz thz frequencies"
    - "privacy preserving and collusion resistant charging coordination schemes for smart grid"
    - "a vision of 6g wireless systems applications trends technologies and open research problems"
    - "cellular connectivity for uavs network modeling performance analysis and design guidelines"

Connected through hyperedge HE-2 (induced by source paper "optimizing joint probabilistic caching and channel access for clustered d2d networks"):
  with members:
    - "performance analysis of mobile cellular connected drones under practical antenna configurations"
    - "privacy preserving smart parking system using blockchain and private information retrieval"
    - "on the reliability of wireless virtual reality at terahertz thz frequencies"
    - "privacy preserving and collusion resistant charging coordination schemes for smart grid"
    - "mimic learning to generate a shareable network intrusion detection model"
    - "mobility in the sky performance and mobility analysis for cellular connected uavs"
    - "blockchain based firmware update scheme tailored for autonomous vehicles"
    - "inter cluster cooperation for wireless d2d caching networks"

Connected through hyperedge HE-3 (induced by source paper "practical fast gradient sign attack against mammographic image classifier"):
  with members:
    - "privacy preserving smart parking system using blockchain and private information retrieval"
    - "b ride ride sharing with privacy preservation trust and fair payment atop public blockchain"
    - "privacy preserving and collusion resistant charging coordination schemes for smart grid"
    - "on sharing models instead of data using mimic learning for smart health applications"
    - "expansion of cyber attack data from unbalanced datasets using generative techniques"
    - "blockchain based charging coordination mechanism for smart grid energy storage units"
    - "adversarial examples are not easily detected bypassing ten detection methods"
    - "analysis of universal adversarial perturbations"

Connected through hyperedge HE-4 (induced by source paper "on sharing models instead of data using mimic learning for smart health applications"):
  with members:
    - "privacy preserving smart parking system using blockchain and private information retrieval"
    - "b ride ride sharing with privacy preservation trust and fair payment atop public blockchain"
    - "on the reliability of wireless virtual reality at terahertz thz frequencies"
    - "privacy preserving and collusion resistant charging coordination schemes for smart grid"
    - "mimic learning to generate a shareable network intrusion detection model"
    - "expansion of cyber attack data from unbalanced datasets using generative techniques"
    - "mobility in the sky performance and mobility analysis for cellular connected uavs"
    - "deep ehr a survey of recent advances in deep learning techniques for electronic health record ehr analysis"

Connected through hyperedge HE-5 (induced by source paper "2l 3w 2 level 3 way hardware software co verification for the mapping of deep learning architecture dla onto fpga boards"):
  with members:
    - "privacy preserving smart parking system using blockchain and private information retrieval"
    - "b ride ride sharing with privacy preservation trust and fair payment atop public blockchain"
    - "privacy preserving and collusion resistant charging coordination schemes for smart grid"
    - "on sharing models instead of data using mimic learning for smart health applications"
    - "mimic learning to generate a shareable network intrusion detection model"
    - "a stealthy hardware trojan exploiting the architectural vulnerability of deep learning architectures input interception attack iia"
    - "a scalable multilabel classification to deploy deep learning architectures for edge devices"
    - "fpga dnn co design an efficient design methodology for iot intelligence on the edge"

Connected through hyperedge HE-6 (induced by source paper "expansion of cyber attack data from unbalanced datasets using generative techniques"):
  with members:
    - "privacy preserving smart parking system using blockchain and private information retrieval"
    - "b ride ride sharing with privacy preservation trust and fair payment atop public blockchain"
    - "on sharing models instead of data using mimic learning for smart health applications"
    - "blockchain based firmware update scheme tailored for autonomous vehicles"
    - "bagan data augmentation with balancing gan"
    - "blockchain based charging coordination mechanism for smart grid energy storage units"
    - "generalization of deep neural networks for chest pathology classification in x rays using generative adversarial networks"
    - "adversarial examples in the physical world"

Connected through hyperedge HE-7 (induced by source paper "a scalable multilabel classification to deploy deep learning architectures for edge devices"):
  with members:
    - "privacy preserving smart parking system using blockchain and private information retrieval"
    - "b ride ride sharing with privacy preservation trust and fair payment atop public blockchain"
    - "privacy preserving and collusion resistant charging coordination schemes for smart grid"
    - "a stealthy hardware trojan exploiting the architectural vulnerability of deep learning architectures input interception attack iia"
    - "blockchain based firmware update scheme tailored for autonomous vehicles"
    - "blockchain based charging coordination mechanism for smart grid energy storage units"
    - "recent trends in deep learning based natural language processing"
    - "cnn rnn a unified framework for multi label image classification"

Connected through hyperedge HE-8 (induced by source paper "a stealthy hardware trojan exploiting the architectural vulnerability of deep learning architectures input interception attack iia"):
  with members:
    - "privacy preserving smart parking system using blockchain and private information retrieval"
    - "b ride ride sharing with privacy preservation trust and fair payment atop public blockchain"
    - "privacy preserving and collusion resistant charging coordination schemes for smart grid"
    - "blockchain based firmware update scheme tailored for autonomous vehicles"
    - "potrojan powerful neural level trojan designs in deep learning models"
    - "blockchain based charging coordination mechanism for smart grid energy storage units"
    - "hardware trojan attacks on neural networks"

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)