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 game theoretic model for defending against stealthy attacks with limited resources"
  Abstract: Stealthy attacks are a major threat to cyber security. In practice, both attackers and defenders have resource constraints that could limit their capabilities. Hence, to develop robust defense strategies, a promising approach is to utilize game theory to understand the fundamental trade-offs involved. Previous works in this direction, however, mainly focus on the single-node case without considering strict resource constraints. In this paper, a game-theoretic model for protecting a system of multiple nodes against stealthy attacks is proposed. We consider the practical setting where the frequencies of both attack and defense are constrained by limited resources, and an asymmetric feedback structure where the attacker can fully observe the states of nodes while largely hiding its actions from the defender. We characterize the best response strategies for both attacker and defender, and study the Nash Equilibria of the game. We further study a sequential game where the defender first announces its strategy and the attacker then responds accordingly, and design an algorithm that finds a nearly optimal strategy for the defender to commit to.

Connected through hyperedge HE-1 (induced by source paper "flipin a game theoretic cyber insurance framework for incentive compatible cyber risk management of internet of things"):
  with members:
    - "dynamic psychological game theory for secure internet of battlefield things iobt systems"
    - "defense against advanced persistent threats in dynamic cloud storage a colonel blotto game approach"
    - "dynamic connectivity game for adversarial internet of battlefield things systems"
    - "a colonel blotto game for interdependence aware cyber physical systems security in smart cities"
    - "moving target defense for web applications using bayesian stackelberg games"
    - "jamming in the internet of things a game theoretic perspective"
    - "flip the cloud cyber physical signaling games in the presence of advanced persistent threats"
    - "internet of things iot a vision architectural elements and future directions"

Connected through hyperedge HE-2 (induced by source paper "a dynamic games approach to proactive defense strategies against advanced persistent threats in cyber physical systems"):
  with members:
    - "adaptive honeypot engagement through reinforcement learning of semi markov decision processes"
    - "adaptive strategic cyber defense for advanced persistent threats in critical infrastructure networks"
    - "istrict an interdependent strategic trust mechanism for the cloud enabled internet of controlled things"
    - "a composite metric based path selection technique for the tor anonymity network"
    - "a game theoretic taxonomy and survey of defensive deception for cybersecurity and privacy"

Connected through hyperedge HE-3 (induced by source paper "optimal timing of moving target defense a stackelberg game model"):
  with members:
    - "a game theoretic taxonomy and survey of defensive deception for cybersecurity and privacy"
    - "when to reset your keys optimal timing of security updates via learning"

Connected through hyperedge HE-4 (induced by source paper "defense against advanced persistent threats in dynamic cloud storage a colonel blotto game approach"):
  with members:
    - "jamming in the internet of things a game theoretic perspective"
    - "when to reset your keys optimal timing of security updates via learning"
    - "flip the cloud cyber physical signaling games in the presence of advanced persistent threats"
    - "playing atari with deep reinforcement learning"
    - "reinforcement learning a survey"

Connected through hyperedge HE-5 (induced by source paper "on a generic security game model"):
  with members:
    - "interdependent security games on networks under behavioral probability weighting"
    - "optimizing active cyber defense"
    - "quantitative analysis of active cyber defenses based on temporal platform diversity"
    - "settling the complexity of computing two player nash equilibria"

Connected through hyperedge HE-6 (induced by source paper "defending against stealthy attacks on multiple nodes with limited resources a game theoretic analysis"):
  with members:
    - "when to reset your keys optimal timing of security updates via learning"

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.GT(Computer Science and Game Theory)