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 "toward k connectivity of the random graph induced by a pairwise key predistribution scheme with unreliable links"):
  Abstract: We study the secure and reliable connectivity of wireless sensor networks. Security is assumed to be ensured by the random pairwise key predistribution scheme of Chan, Perrig, and Song, and unreliable wireless links are represented by independent ON/OFF channels. Modeling the network by an intersection of a random    $K$   -out graph and an Erdős–Renyi graph, we present scaling conditions (on the number of nodes    $n$   , the scheme parameter    $K$   , and the probability    $p$    of a wireless channel being on), such that the resulting graph contains no nodes with a degree less than    $k$    with high probability. Results are given in the form of zero–one laws with    $n$    getting large, and are shown to improve the previous results by Yagan and Makowski on the absence of isolated nodes (i.e., absence of nodes with degree zero) in the same model. Through simulations, the established zero–one laws are also shown to hold for the property of    $k$   -connectivity, i.e., the property that graph remains connected despite the deletion of any    $k-1$    nodes or edges.

Includes members:
  Member "k connectivity in random key graphs with unreliable links":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "on the strength of connectivity of inhomogeneous random k out graphs")
  Member "on topological properties of wireless sensor networks under the q composite key predistribution scheme with on off channels":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "secure communication in dynamic wireless ad hoc networks")
  Member "modeling the pairwise key predistribution scheme in the presence of unreliable links":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "on the strength of connectivity of inhomogeneous random k out graphs")
  Member "k connectivity in secure wireless sensor networks with physical link constraints the on off channel model":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "k connectivity in random key graphs with unreliable links")
  Member "performance of the eschenauer gligor key distribution scheme under an on off channel":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "k connectivity in random key graphs with unreliable links")

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.DM(Discrete Mathematics)