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: "b ride ride sharing with privacy preservation trust and fair payment atop public blockchain"
  Abstract: Ride-sharing is a service that enables drivers to share their trips with other riders, contributing to appealing benefits of shared travel costs. However, the majority of existing platforms rely on a central third party, which make them subject to a single point of failure and privacy disclosure issues. Moreover, they are vulnerable to DDoS and Sybil attacks due to malicious users involvement. Besides, high fees should be paid to the service provider. In this paper, we propose a decentralized ride-sharing service based on public Blockchain, named B-Ride. Both riders and drivers can find rides match while preserving their trip data, including pick-up/drop-off location, and departure/arrival date. However, under the anonymity of the public blockchain, a malicious user may submit multiple ride requests or offers, while not committing to any of them, to discover better offer or to make the system unreliable. B-Ride solves this problem by introducing a time-locked deposit protocol for a ride-sharing by leveraging smart contract and zero-knowledge set membership proof. In a nutshell, both a driver and a rider have to show their commitment by sending a deposit to the blockchain. Later, a driver has to prove to the blockchain on the agreed departure time that he has arrived at the pick-up location. To preserve rider/driver location privacy by hiding the exact pick-up location, the proof is done using zero-knowledge set membership protocol. Moreover, to ensure a fair payment, a pay-as-you-drive methodology is introduced based on the elapsed distance of the driver and the rider. Also, we introduce a reputation-based trust model to rate drivers based on their past trips to allow riders to select them based on their history on the system. Finally, we implement B-Ride in a test net of Ethereum. The experiment results show the applicability of our protocol atop the existing real-world blockchain.

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"
    - "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 "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"
    - "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-3 (induced by source paper "attribute based multi signature and encryption for ehr management a blockchain based solution"):
  with members:
    - "access control for electronic health records with hybrid blockchain edge architecture"
    - "multi authority attribute based access control with smart contract"
    - "blockchain based firmware update scheme tailored for autonomous vehicles"
    - "secure and trustable electronic medical records sharing using blockchain"

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"
    - "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:
    - "detecting sybil attacks using proofs of work and location in vanets"
    - "privacy preserving smart parking system using blockchain and private information retrieval"
    - "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:
    - "detecting sybil attacks using proofs of work and location in vanets"
    - "privacy preserving smart parking system using blockchain and private information retrieval"
    - "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:
    - "detecting sybil attacks using proofs of work and location in vanets"
    - "privacy preserving smart parking system using blockchain and private information retrieval"
    - "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:
    - "detecting sybil attacks using proofs of work and location in vanets"
    - "privacy preserving smart parking system using blockchain and private information retrieval"
    - "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)