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: "privacy preserving and collusion resistant charging coordination schemes for smart grid"
  Abstract: Energy storage units (ESUs) including EVs and home batteries enable several attractive features of the modern smart grids such as effective demand response and reduced electric bills. However, uncoordinated charging of ESUs stresses the power system. In this paper, we propose privacy-preserving and collusion-resistant charging coordination centralized and decentralized schemes for the smart grid. The centralized scheme is used in case of robust communication infrastructure that connects the ESUs to the utility, while the decentralized scheme is useful in case of infrastructure not available or costly. In the centralized scheme, each energy storage unit should acquire anonymous tokens from a charging controller (CC) to send multiple charging requests to the CC via the aggregator. CC can use the charging requests to enough data to run the charging coordination scheme, but it cannot link the data to particular ESUs or reveal any private information. Our centralized scheme uses a modified knapsack problem formulation technique to maximize the amount of power delivered to the ESUs before the charging requests expire without exceeding the available maximum charging capacity. In the decentralized scheme, several ESUs run the scheme in a distributed way with no need to aggregator or CC. One ESU is selected as a head node that should decrypt the ciphertext of the aggregated messages of the ESUs' messages and broadcast it to the community while not revealing the ESUs' individual charging demands. Then, ESUs can coordinate charging requests based on the aggregated charging demand while not exceeding the maximum charging capacity. Extensive experiments and simulations are conducted to demonstrate that our schemes are efficient and secure against various attacks, and can preserve ESU owner's privacy.

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"
    - "detecting sybil attacks using proofs of work and location in vanets"
    - "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"
    - "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"
    - "detecting sybil attacks using proofs of work and location in vanets"
    - "privacy preserving smart parking system using blockchain and private information retrieval"
    - "on the reliability of wireless virtual reality at terahertz thz frequencies"
    - "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:
    - "detecting sybil attacks using proofs of work and location in vanets"
    - "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"
    - "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:
    - "detecting sybil attacks using proofs of work and location in vanets"
    - "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"
    - "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:
    - "detecting sybil attacks using proofs of work and location in vanets"
    - "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"
    - "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 "a scalable multilabel classification to deploy deep learning architectures for edge devices"):
  with members:
    - "detecting sybil attacks using proofs of work and location in vanets"
    - "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"
    - "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-7 (induced by source paper "a stealthy hardware trojan exploiting the architectural vulnerability of deep learning architectures input interception attack iia"):
  with members:
    - "detecting sybil attacks using proofs of work and location in vanets"
    - "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"
    - "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"

Connected through hyperedge HE-8 (induced by source paper "mimic learning to generate a shareable network intrusion detection model"):
  with members:
    - "detecting sybil attacks using proofs of work and location in vanets"
    - "privacy preserving smart parking system using blockchain and private information retrieval"
    - "blockchain based firmware update scheme tailored for autonomous vehicles"
    - "blockchain based charging coordination mechanism for smart grid energy storage units"
    - "neural ranking models with weak supervision"
    - "share your model instead of your data privacy preserving mimic learning for ranking"

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)