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 "random intersection graphs and their applications in security wireless communication and social networks"):
  Abstract: Random intersection graphs have received much interest and been used in diverse applications. They are naturally induced in modeling secure sensor networks under random key predistribution schemes, as well as in modeling the topologies of social networks including common-interest networks, collaboration networks, and actor networks. Simply put, a random intersection graph is constructed by assigning each node a set of items in some random manner and then putting an edge between any two nodes that share a certain number of items. #R##N#Broadly speaking, our work is about analyzing random intersection graphs, and models generated by composing it with other random graph models including random geometric graphs and Erd\H{o}s-R\'enyi graphs. These compositional models are introduced to capture the characteristics of various complex natural or man-made networks more accurately than the existing models in the literature. For random intersection graphs and their compositions with other random graphs, we study properties such as ($k$-)connectivity, ($k$-)robustness, and containment of perfect matchings and Hamilton cycles. Our results are typically given in the form of asymptotically exact probabilities or zero-one laws specifying critical scalings, and provide key insights into the design and analysis of various real-world networks.

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 "designing securely and reliably connected wireless sensor networks":
    also connected through other hyperedges:
      (none)
  Member "connectivity in secure wireless sensor networks under transmission constraints":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "secure communication in dynamic wireless ad hoc networks")
  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-3 (induced by source paper "secure communication in dynamic wireless ad hoc networks")
  Member "on the strengths of connectivity and robustness in general random intersection graphs":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "k connectivity in random key graphs with unreliable links")
  Member "the phase transition in inhomogeneous random intersection graphs":
    also connected through other hyperedges:
      - Hyperedge HE-5 (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-6 (induced by source paper "determining r and r s robustness of digraphs using mixed integer linear programming")
  Member "k connectivity in secure wireless sensor networks with physical link constraints the on off channel model":
    also connected through other hyperedges:
      - Hyperedge HE-7 (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)