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 "cross chain deals and adversarial commerce"):
  Abstract: Modern distributed data management systems face a new challenge: how can autonomous, mutually-distrusting parties cooperate safely and effectively? Addressing this challenge brings up questions familiar from classical distributed systems: how to combine multiple steps into a single atomic action, how to recover from failures, and how to synchronize concurrent access to data. Nevertheless, each of these issues requires rethinking when participants are autonomous and potentially adversarial. #R##N#We propose the notion of a \emph{cross-chain deal}, a new way to structure complex distributed computations in an adversarial setting. Deals are inspired by classical atomic transactions, but are necessarily different, in important ways, to accommodate the decentralized and untrusting nature of the exchange. We describe novel safety and liveness properties, along with two alternative protocols for implementing cross-chain deals in a system of independent blockchain ledgers. One protocol, based on synchronous communication, is fully decentralized, while the other, based on eventually-synchronous communication, necessarily requires stronger trust assumptions.

Includes members:
  Member "atomic commitment across blockchains":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "distributed cross blockchain transactions")
  Member "hyperledger fabric a distributed operating system for permissioned blockchains":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "tenderbake classical bft style consensus for public blockchains")
  Member "atomic cross chain swaps":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "throughput optimal routing in blockchain based payment systems")
  Member "chainspace a sharded smart contracts platform":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "surface a practical blockchain consensus algorithm for real world networks")
  Member "decentralizing authorities into scalable strongest link cothorities":
    also connected through other hyperedges:
      (none)
  Member "augur a decentralized open source platform for prediction markets":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "blockchain based decentralized applications technology review and development guidelines")

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.DC(Distributed, Parallel, and Cluster Computing)