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: "on the effectiveness of the truth spreading rumor blocking strategy for restraining rumors"
  Abstract: Spreading truths and blocking rumors are two typical strategies for inhibiting rumors. In practice, a tradeoff between the two strategies, which is known as the TSRB strategy, may achieve a better cost-effectiveness. This paper is devoted to assessing the effectiveness of the TSRB strategy. For that purpose, an individual-level spreading model (the generic URQT model) capturing the interaction between a rumor and the truth is established. Under the model, a set of criteria for the dying out of a rumor is presented. These criteria capture the combined influence of the basic parameters and the network structures on the effectiveness of the TSRB strategy. Experimental results show that, when the rumor dies out, the dynamics of a simplified URQT model (the linear URQT model) fits well with the actual rumor-truth interacting process. Therefore, the generic URQT model and sometimes the linear URQT model provide a proper basis for assessing the effectiveness of the TSRB strategy.

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"
    - "distributed interaction between computer virus and patch a modeling study"
    - "analysis of the effectiveness of the truth spreading strategy for inhibiting 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:
    - "distributed interaction between computer virus and patch a modeling study"
    - "analysis of the effectiveness of the truth spreading strategy for inhibiting 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)