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 "sef a secure fountain architecture for slashing storage costs in blockchains"):
  Abstract: Full nodes, which synchronize the entire blockchain history and independently validate all the blocks, form the backbone of any blockchain network by playing a vital role in ensuring security properties. On the other hand, a user running a full node needs to pay a heavy price in terms of storage costs. E.g., the Bitcoin blockchain size has grown over 215GB, in spite of its low throughput. The ledger size for a high throughput blockchain Ripple has already reached 9TB, and it is growing at an astonishing rate of 12GB per day! #R##N#In this paper, we propose an architecture based on 'fountain codes', a class of erasure codes, that enables any full node to 'encode' validated blocks into a small number of 'coded blocks', thereby reducing its storage costs by orders of magnitude. In particular, our proposed "Secure Fountain (SeF)" architecture can achieve a near-optimal trade-off between the storage savings per node and the 'bootstrap cost' in terms of the number of (honest) storage-constrained nodes a new node needs to contact to recover the blockchain. A key technical innovation in SeF codes is to make fountain codes secure against adversarial nodes that can provide maliciously formed coded blocks. Our idea is to use the header-chain as a 'side-information' to check whether a coded block is maliciously formed while it is getting decoded. Further, the 'rateless property' of fountain codes helps in achieving high decentralization and scalability. Our experiments demonstrate that SeF codes tuned to achieve 1000x storage savings enable full nodes to encode the 191GB Bitcoin blockchain into 195MB on average. A new node can recover the blockchain from an arbitrary set of storage-constrained nodes as long as the set contains ~1100 honest nodes on average. Note that for a 1000x storage savings, the fundamental bound on the number of honest nodes to contact is 1000: we need about 10% more in practice.

Includes members:
  Member "polyshard coded sharding achieves linearly scaling efficiency and security simultaneously":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "on the feasibility of sybil attacks in shard based permissionless blockchains")
  Member "erasure code based low storage blockchain node":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "coded merkle tree solving data availability attacks in blockchains")
  Member "consensus in the age of blockchains":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "hushrelay a privacy preserving efficient and scalable routing algorithm for off chain payments")
  Member "dynamic distributed storage for scaling blockchains":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "coded merkle tree solving data availability attacks in blockchains")
  Member "solida a blockchain protocol based on reconfigurable byzantine consensus":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "on the feasibility of sybil attacks in shard based permissionless blockchains")
  Member "a survey on network codes for distributed storage":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "a combinatorial view of the service rates of codes problem its equivalence to fractional matching and its connection with batch codes")
  Member "efficient erasure decoding of reed solomon codes":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "hierarchical coded matrix multiplication")

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)