human: Given a hyperedge-centered hypergraph: <hypergraph>, where the center hyperedge is induced by one source paper and its member nodes are the cited papers.

Details of the hypergraph:
Center hyperedge (induced by source paper "barracuda the power of ell polling in proof of stake blockchains"):
  Abstract: A blockchain is a database of sequential events that is maintained by a distributed group of nodes. A key consensus problem in blockchains is that of determining the next block (data element) in the sequence. Many blockchains address this by electing a new node to propose each new block. The new block is (typically) appended to the tip of the proposer's local blockchain, and subsequently broadcast to the rest of the network. Without network delay (or adversarial behavior), this procedure would give a perfect chain, since each proposer would have the same view of the blockchain. A major challenge in practice is forking. Due to network delays, a proposer may not yet have the most recent block, and may, therefore, create a side chain that branches from the middle of the main chain. Forking reduces throughput, since only one a single main chain can survive, and all other blocks are discarded. We propose a new P2P protocol for blockchains called Barracuda, in which each proposer, prior to proposing a block, polls $\ell$ other nodes for their local blocktree information. Under a stochastic network model, we prove that this lightweight primitive improves throughput as if the entire network were a factor of $\ell$ faster. We provide guidelines on how to implement Barracuda in practice, guaranteeing robustness against several real-world factors.

Includes members:
  Member "global majority consensus by local majority polling on graphs of a given degree sequence":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "communication cost of consensus for nodes with limited memory")
  Member "deconstructing the blockchain to approach physical limits":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "surface a practical blockchain consensus algorithm for real world networks")
  Member "scaling nakamoto consensus to thousands of transactions per second":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "surface a practical blockchain consensus algorithm for real world networks")
  Member "casper the friendly finality gadget":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "surface a practical blockchain consensus algorithm for real world networks")
  Member "enhancing bitcoin security and performance with strong consistency via collective signing":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "surface a practical blockchain consensus algorithm for real world networks")
  Member "bitcoin ng a scalable blockchain protocol":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "surface a practical blockchain consensus algorithm for real world networks")
  Member "deanonymisation of clients in bitcoin p2p network":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "characterizing eosio blockchain")
  Member "majority is not enough bitcoin mining is vulnerable":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "on the convergence of artificial intelligence and distributed ledger technology a scoping review and future research agenda")

Question: Please tell me which class the source paper 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)