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: "blockbench a framework for analyzing private blockchains"
  Abstract: Blockchain technologies are taking the world by storm. Public blockchains, such as Bitcoin and Ethereum, enable secure peer-to-peer applications like crypto-currency or smart contracts. Their security and performance are well studied. This paper concerns recent private blockchain systems designed with stronger security (trust) assumption and performance requirement. These systems target and aim to disrupt applications which have so far been implemented on top of database systems, for example banking, finance applications. Multiple platforms for private blockchains are being actively developed and fine tuned. However, there is a clear lack of a systematic framework with which different systems can be analyzed and compared against each other. Such a framework can be used to assess blockchains' viability as another distributed data processing platform, while helping developers to identify bottlenecks and accordingly improve their platforms. #R##N#In this paper, we first describe BlockBench, the first evaluation framework for analyzing private blockchains. It serves as a fair means of comparison for different platforms and enables deeper understanding of different system design choices. Any private blockchain can be integrated to BlockBench via simple APIs and benchmarked against workloads that are based on real and synthetic smart contracts. BlockBench measures overall and component-wise performance in terms of throughput, latency, scalability and fault-tolerance. Next, we use BlockBench to conduct comprehensive evaluation of three major private blockchains: Ethereum, Parity and Hyperledger Fabric. The results demonstrate that these systems are still far from displacing current database systems in traditional data processing workloads. Furthermore, there are gaps in performance among the three systems which are attributed to the design choices at different layers of the software stack.

Connected through hyperedge HE-1 (induced by source paper "effective scaling of blockchain beyond consensus innovations and moore s law"):
  with members:
    - "concurrency and privacy with payment channel networks"
    - "scalable byzantine consensus via hardware assisted secret sharing"
    - "blockchain goes green an analysis of blockchain on low power nodes"
    - "an energy efficient reconfigurable dtls cryptographic engine for securing internet of things applications"
    - "morph an adaptive framework for efficient and byzantine fault tolerant sdn control plane"
    - "towards scaling blockchain systems via sharding"
    - "a scale out blockchain for value transfer with spontaneous sharding"
    - "scaling nakamoto consensus to thousands of transactions per second"

Connected through hyperedge HE-2 (induced by source paper "on exploiting transaction concurrency to speed up blockchains"):
  with members:
    - "blockchains and distributed databases a twin study"
    - "the security reference architecture for blockchains towards a standardized model for studying vulnerabilities threats and defenses"
    - "an empirical study of speculative concurrency in ethereum smart contracts"
    - "hotstuff bft consensus in the lens of blockchain"
    - "a concurrent perspective on smart contracts"
    - "adding concurrency to smart contracts"
    - "untangling blockchain a data processing view of blockchain systems"

Connected through hyperedge HE-3 (induced by source paper "resilientdb global scale resilient blockchain fabric"):
  with members:
    - "proof of execution reaching consensus through fault tolerant speculation"
    - "towards scaling blockchain systems via sharding"
    - "enhancing bitcoin security and performance with strong consistency via collective signing"
    - "bitcoin ng a scalable blockchain protocol"

Connected through hyperedge HE-4 (induced by source paper "xox fabric a hybrid approach to blockchain transaction execution"):
  with members:
    - "parblockchain leveraging transaction parallelism in permissioned blockchain systems"
    - "fastfabric scaling hyperledger fabric to 20 000 transactions per second"
    - "hyperledger fabric a distributed operating system for permissioned blockchains"

Connected through hyperedge HE-5 (induced by source paper "analysis of indexing structures for immutable data"):
  with members:
    - "untangling blockchain a data processing view of blockchain systems"
    - "datahub collaborative data science dataset version management at scale"
    - "a critique of ansi sql isolation levels"

Connected through hyperedge HE-6 (induced by source paper "performance modeling and analysis of a hyperledger based system using gspn"):
  with members:
    - "hyperledger fabric a distributed operating system for permissioned blockchains"
    - "performance benchmarking and optimizing hyperledger fabric blockchain platform"

Connected through hyperedge HE-7 (induced by source paper "local bitcoin network simulator for performance evaluation using lightweight virtualization"):
  with members:
    - "simblock a blockchain network simulator"

Connected through hyperedge HE-8 (induced by source paper "exploring the attack surface of blockchain a systematic overview"):
  with members:
    - "scalable byzantine consensus via hardware assisted secret sharing"
    - "security services using blockchains a state of the art survey"
    - "a survey on the security of blockchain systems"
    - "an empirical analysis of anonymity in zcash"
    - "towards blockchain driven secure and transparent audit logs"
    - "end to end analysis of in browser cryptojacking"
    - "linbft linear communication byzantine fault tolerance for public blockchains"
    - "a survey on security and privacy issues of bitcoin"

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.DB(Databases)