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: "building scalable decentralized payment systems"
  Abstract: Increasing the transactional throughput of decentralized blockchains in a secure manner has been the holy grail of blockchain research for most of the past decade. This paper introduces a scheme for scaling blockchains while retaining virtually identical security and decentralization, and discusses requirements for deploying such a solution in practice. We propose a layer-2 scaling technique using a permissionless side chain with merged block production similar to merged mining. The side chain only supports functionality to transact UTXOs and transfer funds to and from a parent chain in a practically trustless manner. Optimized implementation and engineering of client code, along with improvements to block propagation efficiency versus currently deployed systems, allow this side chain to scale well beyond the capacities exhibited by contemporary blockchains. Finally, a discussion on navigating the complex political landscape of the present-day blockchain space is explored in order to develop compelling steps towards deploying such a side chain in real-world conditions.

Connected through hyperedge HE-1 (induced by source paper "privacy preserving blockchain based federated learning with differential data sharing"):
  with members:
    - "distributed federated learning for ultra reliable low latency vehicular communications"
    - "a tutorial on computing t closeness"
    - "privacy preserving deep learning via weight transmission"
    - "a secure and robust scheme for sharing confidential information in iot systems"
    - "towards federated learning at scale system design"
    - "federated machine learning concept and applications"
    - "chiron privacy preserving machine learning as a service"
    - "privacy loss in apple s implementation of differential privacy on macos 10 12"

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)