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 "on connectivity and robustness in random intersection graphs"):
  Abstract: Random intersection graphs have received much attention recently and been used in a wide range of applications ranging from key predistribution in wireless sensor networks to modeling social networks. For these graphs, each node is equipped with a set of objects in a random manner, and two nodes have an undirected edge in between if they have at least one object in common. In this paper, we investigate connectivity and robustness in a  general random intersection graph  model. Specifically, we establish sharp asymptotic zero-one laws for    $k$  -connectivity and    $k$  -robustness, as well as the asymptotically exact probability of    $k$  -connectivity, for any positive integer    $k$  . The   $k$   -connectivity property quantifies how resilient is the connectivity of a graph against node or edge failures, while   $k$  -robustness measures the effectiveness of  local-information-based  consensus algorithms (which do not use global graph topology information) in the presence of adversarial nodes. In addition to presenting the results under the general random intersection graph model, we consider two special cases of the general model, a  binomial  random intersection graph and a  uniform  random intersection graph, which both have numerous applications as well. For these two specialized graphs, we present asymptotically exact probabilities of   $k$  -connectivity and asymptotic zero-one laws for   $k$  -robustness.

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 the strengths of connectivity and robustness in general random intersection graphs":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "k connectivity in random key graphs with unreliable links")
  Member "resilient continuous time consensus in fractional robust networks":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "determining r and r s robustness of digraphs using mixed integer linear programming")
  Member "performance of the eschenauer gligor key distribution scheme under an on off channel":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "k connectivity in random key graphs with unreliable links")
  Member "robustness of complex networks with implications for consensus and contagion":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "the strength of connectivity of random graphs induced by pairwise key predistribution schemes implications on security and reliability of heterogeneous sensor networks")
  Member "robustness of information diffusion algorithms to locally bounded adversaries":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "inner attention supported adaptive cooperation for heterogeneous multi robots teaming based on multi agent reinforcement learning")
  Member "component evolution in general random intersection graphs":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "k connectivity of random graphs and random geometric graphs in node fault model")

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)