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: "characterizing the power of moving target defense via cyber epidemic dynamics"
  Abstract: Moving Target Defense (MTD) can enhance the resilience of cyber systems against attacks. Although there have been many MTD techniques, there is no systematic understanding and {\em quantitative} characterization of the power of MTD. In this paper, we propose to use a cyber epidemic dynamics approach to characterize the power of MTD. We define and investigate two complementary measures that are applicable when the defender aims to deploy MTD to achieve a certain security goal. One measure emphasizes the maximum portion of time during which the system can afford to stay in an undesired configuration (or posture), without considering the cost of deploying MTD. The other measure emphasizes the minimum cost of deploying MTD, while accommodating that the system has to stay in an undesired configuration (or posture) for a given portion of time. Our analytic studies lead to algorithms for optimally deploying MTD.

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"
    - "disease spread over randomly switched large scale networks"

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 "toward proactive adaptive defense a survey on moving target defense"):
  with members:
    - "modeling and analysis of integrated proactive defense mechanisms for internet of things"
    - "moving target defense for deep visual sensing against adversarial examples"
    - "defending via strategic ml selection"
    - "a survey of moving target defenses for network security"
    - "frvm flexible random virtual ip multiplexing in software defined networks"
    - "cost benefit analysis of moving target defense in power grids"
    - "markov game modeling of moving target defense for strategic detection of threats in cloud networks"
    - "mtdeep boosting the security of deep neural nets against adversarial attacks with moving target defense"

Connected through hyperedge HE-5 (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"
    - "preventive and reactive cyber defense dynamics is globally stable"
    - "spatiotemporal patterns and predictability of cyberattacks"

Connected through hyperedge HE-6 (induced by source paper "a survey on security metrics"):
  with members:
    - "characterizing honeypot captured cyber attacks statistical framework and case study"
    - "a stochastic model of active cyber defense dynamics"
    - "a characterization of cybersecurity posture from network telescope data"
    - "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"
    - "active cyber defense dynamics exhibiting rich phenomena"

Connected through hyperedge HE-7 (induced by source paper "preventive and reactive cyber defense dynamics is globally stable"):
  with members:
    - "a stochastic model of active cyber defense dynamics"
    - "a stochastic model for quantitative security analyses of networked systems"
    - "an extended stochastic model for quantitative security analysis of networked systems"
    - "cyber epidemic models with dependences"
    - "a new approach to modeling and analyzing security of networked systems"
    - "active cyber defense dynamics exhibiting rich phenomena"

Connected through hyperedge HE-8 (induced by source paper "active cyber defense dynamics exhibiting rich phenomena"):
  with members:
    - "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"
    - "a new approach to modeling and analyzing security of networked systems"

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)