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: "preventive and reactive cyber defense dynamics is globally stable"
  Abstract: The recently proposed {\em cybersecurity dynamics} approach aims to understand cybersecurity from a holistic perspective by modeling the evolution of the global cybersecurity state. These models describe the interactions between the various kinds of cyber defenses and the various kinds of cyber attacks. We study a particular kind of cybersecurity dynamics caused by the interactions between preventive and reactive defenses (e.g., filtering and malware detection) against push- and pull-based cyber attacks (e.g., malware spreading and "drive-by download" attacks). The dynamics was previously shown to be globally stable in a {\em special} regime of the parameter universe, but little is known beyond this special regime. In this paper, we resolve an open problem in this domain by proving that the dynamics is globally stable in the {\em entire} parameter universe (i.e., the dynamics always converges to a unique equilibrium). We discuss the cybersecurity meanings and implications of this theoretic result. We also prove that the dynamics converges {\em exponentially} to the equilibrium except for a special parameter regime, in which case the dynamics converges {\em polynomially}. Since it is often difficult to compute the equilibrium, we propose new bounds of the equilibrium and numerically show that these bounds are tighter than those proposed in the literature.

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"
    - "epidemic threshold of an sis model in dynamic switching networks"
    - "disease spread over randomly switched large scale networks"
    - "characterizing the power of moving target defense via cyber epidemic dynamics"

Connected through hyperedge HE-2 (induced by source paper "a survey on ethereum systems security vulnerabilities attacks and defenses"):
  with members:
    - "security and privacy on blockchain"
    - "exploring the attack surface of blockchain a systematic overview"
    - "a survey on consensus mechanisms and mining strategy management in blockchain networks"
    - "metrics towards measuring cyber agility"
    - "selfish mining in ethereum"
    - "a survey of distributed consensus protocols for blockchain networks"
    - "finding the greedy prodigal and suicidal contracts at scale"
    - "ethir a framework for high level analysis of ethereum bytecode"

Connected through hyperedge HE-3 (induced by source paper "metrics towards measuring cyber agility"):
  with members:
    - "characterizing honeypot captured cyber attacks statistical framework and case study"
    - "a stochastic model of active cyber defense dynamics"
    - "push and pull based epidemic spreading in networks thresholds and deeper insights"
    - "optimizing active cyber defense"
    - "an extended stochastic model for quantitative security analysis of networked systems"
    - "predicting cyber attack rates with extreme values"
    - "cyber epidemic models with dependences"
    - "a new approach to modeling and analyzing security of networked systems"

Connected through hyperedge HE-4 (induced by source paper "a case study on using deep learning for network intrusion detection"):
  with members:
    - "metrics towards measuring cyber agility"
    - "vuldeepecker a deep learning based system for vulnerability detection"
    - "a novel hierarchical intrusion detection system based on decision tree and rules based models"
    - "characterizing honeypot captured cyber attacks statistical framework and case study"
    - "entity embeddings of categorical variables"
    - "predicting cyber attack rates with extreme values"
    - "spatiotemporal patterns and predictability of cyberattacks"
    - "characterizing the power of moving target defense via cyber epidemic dynamics"

Connected through hyperedge HE-5 (induced by source paper "node diversification in complex networks by decentralized colouring"):
  with members:
    - "push and pull based epidemic spreading in networks thresholds and deeper insights"
    - "active cyber defense dynamics exhibiting rich phenomena"
    - "distributed deterministic edge coloring using bounded neighborhood independence"

Connected through hyperedge HE-6 (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"
    - "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"

Connected through hyperedge HE-7 (induced by source paper "defend against advanced persistent threats an optimal control approach"):
  with members:
    - "a stochastic model of active cyber defense dynamics"
    - "push and pull based epidemic spreading in networks thresholds and deeper insights"

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.CR(Cryptography and Security)