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: "nosebreak attacking honeynets"
  Abstract: It is usually assumed that honeynets are hard to detect and that attempts to detect or disable them can be unconditionally monitored. We scrutinize this assumption and demonstrate a method how a host in a honeynet can be completely controlled by an attacker without any substantial logging taking place.

Connected through hyperedge HE-1 (induced by source paper "on evaluating the effectiveness of the honeybot a case study"):
  with members:
    - "a survey on honeypot software and data analysis"

Connected through hyperedge HE-2 (induced by source paper "modeling and analysis of leaky deception using signaling games with evidence"):
  with members:
    - "information theoretic approach to strategic communication as a hierarchical game"
    - "a stackelberg game perspective on the conflict between machine learning and data obfuscation"
    - "deception by design evidence based signaling games for network defense"
    - "flip the cloud cyber physical signaling games in the presence of advanced persistent threats"
    - "finding deceptive opinion spam by any stretch of the imagination"

Connected through hyperedge HE-3 (induced by source paper "the dos and don ts of industrial network simulation a field report"):
  with members:
    - "highly scalable and flexible model for effective aggregation of context based data in generic iiot scenarios"
    - "evaluation of machine learning based anomaly detection algorithms on an industrial modbus tcp data set"
    - "towards a flexible architecture for industrial networking"
    - "a question of context enhancing intrusion detection by providing context information"
    - "two decades of scada exploitation a brief history"

Connected through hyperedge HE-4 (induced by source paper "apate a linux kernel module for high interaction honeypots"):
  with members:
    - "the all seeing eye a massive multi sensor zero configuration intrusion detection system for web applications"

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)