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: "distributed interaction between computer virus and patch a modeling study"
  Abstract: The decentralized patch distribution mechanism holds significant promise as an alternative to its centralized counterpart. For the purpose of accurately evaluating the performance of the decentralized patch distribution mechanism and based on the exact SIPS model that accurately captures the average dynamics of the interaction between viruses and patches, a new virus-patch interacting model, which is known as the generic SIPS model, is proposed. This model subsumes the linear SIPS model. The dynamics of the generic SIPS model is studied comprehensively. In particular, a set of criteria for the final extinction or/and long-term survival of viruses or/and patches are presented. Some conditions for the linear SIPS model to accurately capture the average dynamics of the virus-patch interaction are empirically found. As a consequence, the linear SIPS model can be adopted as a standard model for assessing the performance of the distributed patch distribution mechanism, provided the proper conditions are satisfied.

Connected through hyperedge HE-1 (induced by source paper "assessing the risk of advanced persistent threats"):
  with members:
    - "mobile edge computing fog et al a survey and analysis of security threats and challenges"
    - "analysis of the effectiveness of the truth spreading strategy for inhibiting rumors"
    - "on the effectiveness of the truth spreading rumor blocking strategy for restraining rumors"
    - "a discount strategy in word of mouth marketing and its assessment"
    - "a stochastic model of active cyber defense dynamics"
    - "push and pull based epidemic spreading in networks thresholds and deeper insights"
    - "optimizing active cyber defense"
    - "epidemic threshold of an sis model in dynamic switching networks"

Connected through hyperedge HE-2 (induced by source paper "security evaluation of cyber networks under advanced persistent threats"):
  with members:
    - "analysis of the effectiveness of the truth spreading strategy for inhibiting rumors"
    - "on the effectiveness of the truth spreading rumor blocking strategy for restraining rumors"
    - "a discount strategy in word of mouth marketing and its assessment"
    - "a stochastic model of active cyber defense dynamics"
    - "push and pull based epidemic spreading in networks thresholds and deeper insights"
    - "optimizing active cyber defense"
    - "preventive and reactive cyber defense dynamics is globally stable"

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.SI(Social and Information Networks)