human: Given a node-centered hypergraph: <hypergraph>, where nodes represent papers and hyperedges represent sets of papers co-cited by a source paper.

Details of the hypergraph:
Center node: "disease spread over randomly switched large scale networks"
  Abstract: In this paper we study disease spread over a randomly switched network, which is modeled by a stochastic switched differential equation based on the so called Nintertwined model for disease spread over static networks. Assuming that all the edges of the network are independently switched, we present sufficient conditions for the convergence of infection probability to zero. Though the stability theory for switched linear systems can naively derive a sufficient condition for the convergence, the condition cannot be used for large-scale networks because, for a network with n agents, it requires computing the maximum real eigenvalue of a matrix of size exponential in n. On the other hand, our conditions that are based also on the spectral theory of random matrices can be checked by computing the maximum real eigenvalue of a matrix of size n.

Connected through hyperedge HE-1 (induced by source paper "preventive and reactive cyber defense dynamics with ergodic time dependent parameters is globally attractive"):
  with members:
    - "a stochastic model of active cyber defense dynamics"
    - "a stochastic model for quantitative security analyses of networked systems"
    - "a new approach to modeling and analyzing security of networked systems"
    - "active cyber defense dynamics exhibiting rich phenomena"
    - "preventive and reactive cyber defense dynamics is globally stable"
    - "epidemic threshold of an sis model in dynamic switching networks"
    - "characterizing the power of moving target defense via cyber epidemic dynamics"

Connected through hyperedge HE-2 (induced by source paper "contact adaption during epidemics a multilayer network formulation approach"):
  with members:
    - "stability of spreading processes over time varying large scale networks"
    - "epidemic processes over adaptive state dependent networks"
    - "a convex framework for optimal investment on disease awareness in social networks"

Question: Please tell me which class the center node 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.SY(Systems and Control)