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: "game theoretic analysis of cyber deception evidence based strategies and dynamic risk mitigation"
  Abstract: Deception is a technique to mislead human or computer systems by manipulating beliefs and information. For the applications of cyber deception, non-cooperative games become a natural choice of models to capture the adversarial interactions between the players and quantitatively characterizes the conflicting incentives and strategic responses. In this chapter, we provide an overview of deception games in three different environments and extend the baseline signaling game models to include evidence through side-channel knowledge acquisition to capture the information asymmetry, dynamics, and strategic behaviors of deception. We analyze the deception in binary information space based on a signaling game framework with a detector that gives off probabilistic evidence of the deception when the sender acts deceptively. We then focus on a class of continuous one-dimensional information space and take into account the cost of deception in the signaling game. We finally explore the multi-stage incomplete-information Bayesian game model for defensive deception for advanced persistent threats (APTs). We use the perfect Bayesian Nash equilibrium (PBNE) as the solution concept for the deception games and analyze the strategic equilibrium behaviors for both the deceivers and the deceivees.

Connected through hyperedge HE-1 (induced by source paper "game theory for cyber deception a tutorial"):
  with members:
    - "modeling analysis and mitigation of dynamic botnet formation in wireless iot networks"
    - "dynamic bayesian games for adversarial and defensive cyber deception"
    - "adaptive strategic cyber defense for advanced persistent threats in critical infrastructure networks"
    - "game theory meets network security a tutorial"
    - "modeling and analysis of leaky deception using signaling games with evidence"
    - "istrict an interdependent strategic trust mechanism for the cloud enabled internet of controlled things"
    - "a dynamic game analysis and design of infrastructure network protection and recovery 125"
    - "a game theoretic taxonomy and survey of defensive deception for cybersecurity and privacy"

Connected through hyperedge HE-2 (induced by source paper "deceptive reinforcement learning under adversarial manipulations on cost signals"):
  with members:
    - "reinforcement learning with perturbed rewards"
    - "modeling and analysis of leaky deception using signaling games with evidence"
    - "adversarial reinforcement learning framework for benchmarking collision avoidance mechanisms in autonomous vehicles"
    - "istrict an interdependent strategic trust mechanism for the cloud enabled internet of controlled things"
    - "the faults in our pi stars security issues and open challenges in deep reinforcement learning"
    - "optimal timing in dynamic and robust attacker engagement during advanced persistent threats"
    - "reinforcement learning with a corrupted reward channel"
    - "a game theoretic taxonomy and survey of defensive deception for cybersecurity and privacy"

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)