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 "strong secrecy for erasure wiretap channels"):
  Abstract: We show that duals of certain low-density parity-check (LDPC) codes, when used in a standard coset coding scheme, provide strong secrecy over the binary erasure wiretap channel (BEWC). This result hinges on a stopping set analysis of ensembles of LDPC codes with block length n and girth ⋛ for some ⋛. We show that if the minimum left degree of the ensemble is l min , the expected probability of block error is O(1/n⌈l mink/2⌉ −k) when the erasure probability ∊  ef , where ∊ ef  depends on the degree distribution of the ensemble. As long as l min  and k > 2, the dual of this LDPC code provides strong secrecy over a BEWC of erasure probability greater than 1–∊ ef .

Includes members:
  Member "exchange of limits why iterative decoding works":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "scaling exponent of list decoders with applications to polar codes")
  Member "secure nested codes for type ii wiretap channels":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "generalizing multiple access wiretap and wiretap ii channel models achievable rates and cost of strong secrecy")
  Member "applications of ldpc codes to the wiretap channel":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "explicit codes for the wiretap channel a unified design framework")
  Member "finite length scaling for iteratively decoded ldpc ensembles":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "finite length scaling of spatially coupled ldpc codes under window decoding over the bec")

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.IT(Information Theory)