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: "a characterization of cybersecurity posture from network telescope data"
  Abstract: Data-driven understanding of cybersecurity posture is an important problem that has not been adequately explored. In this paper, we analyze some real data collected by CAIDA's network telescope during the month of March 2013. We propose to formalize the concept of cybersecurity posture from the perspectives of three kinds of time series: the number of victims (i.e., telescope IP addresses that are attacked), the number of attackers that are observed by the telescope, and the number of attacks that are observed by the telescope. Characterizing cybersecurity posture therefore becomes investigating the phenomena and statistical properties exhibited by these time series, and explaining their cybersecurity meanings. For example, we propose the concept of {\em sweep-time}, and show that sweep-time should be modeled by stochastic process, rather than random variable. We report that the number of attackers (and attacks) from a certain country dominates the total number of attackers (and attacks) that are observed by the telescope. We also show that substantially smaller network telescopes might not be as useful as a large telescope.

Connected through hyperedge HE-1 (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"
    - "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"
    - "characterizing the power of moving target defense via cyber epidemic dynamics"

Connected through hyperedge HE-2 (induced by source paper "predicting cyber attack rates with extreme values"):
  with members:
    - "characterizing honeypot captured cyber attacks statistical framework and case study"

Connected through hyperedge HE-3 (induced by source paper "regularized maximum correntropy machine"):
  with members:
    - "semantic sparse recoding of visual content for image applications"
    - "document clustering based on max correntropy non negative matrix factorization"
    - "graph regularized non negative matrix factorization by maximizing correntropy"
    - "maximum mutual information regularized classification"
    - "an evasion and counter evasion study in malicious websites detection"
    - "adaptive learning of region based plsa model for total scene annotation"
    - "latent semantic learning with structured sparse representation for human action recognition"
    - "multiple graph regularized protein domain ranking"

Connected through hyperedge HE-4 (induced by source paper "online classifier adaptation for cost sensitive learning"):
  with members:
    - "characterizing honeypot captured cyber attacks statistical framework and case study"
    - "an evasion and counter evasion study in malicious websites detection"
    - "efficient optimization of performance measures by classifier adaptation"
    - "multiple graph regularized protein domain ranking"

Connected through hyperedge HE-5 (induced by source paper "sparse coding with earth mover s distance"):
  with members:
    - "characterizing honeypot captured cyber attacks statistical framework and case study"
    - "an evasion and counter evasion study in malicious websites detection"
    - "exhaustive and efficient constraint propagation a graph based learning approach and its applications"

Connected through hyperedge HE-6 (induced by source paper "representing data by sparse combination of contextual data points for classification"):
  with members:
    - "characterizing honeypot captured cyber attacks statistical framework and case study"
    - "an evasion and counter evasion study in malicious websites detection"
    - "multiple graph regularized protein domain ranking"

Connected through hyperedge HE-7 (induced by source paper "vector quantization by minimizing kullback leibler divergence"):
  with members:
    - "characterizing honeypot captured cyber attacks statistical framework and case study"
    - "an evasion and counter evasion study in malicious websites detection"

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)