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 mean field stackelberg game approach for obfuscation adoption in empirical risk minimization"
  Abstract: Data ecosystems are becoming larger and more complex due to online tracking, wearable computing, and the Internet of Things. But privacy concerns are threatening to erode the potential benefits of these systems. Recently, users have developed obfuscation techniques that issue fake search engine queries, undermine location tracking algorithms, or evade government surveillance. Interestingly, these techniques raise two conflicts: one between each user and the machine learning algorithms which track the users, and one between the users themselves. In this paper, we use game theory to capture the first conflict with a Stackelberg game and the second conflict with a mean field game. We combine both into a dynamic and strategic bi-level framework which quantifies accuracy using empirical risk minimization and privacy using differential privacy. In equilibrium, we identify necessary and sufficient conditions under which 1) each user is incentivized to obfuscate if other users are obfuscating, 2) the tracking algorithm can avoid this by promising a level of privacy protection, and 3) this promise is incentive-compatible for the tracking algorithm.

Connected through hyperedge HE-1 (induced by source paper "prospect theoretic analysis of privacy preserving mechanism"):
  with members:
    - "managing price uncertainty in prosumer centric energy trading a prospect theoretic stackelberg game approach"
    - "reap an efficient incentive mechanism for reconciling aggregation accuracy and individual privacy in crowdsensing"
    - "prospect theory for enhanced cyber physical security of drone delivery systems a network interdiction game"
    - "hardware trojan detection game a prospect theoretic approach"
    - "prospect theory for enhanced smart grid resilience using distributed energy storage"
    - "market model and optimal pricing scheme of big data and internet of things iot"
    - "the value of privacy strategic data subjects incentive mechanisms and fundamental limits"
    - "spectrum investment under uncertainty a behavioral economics perspective"

Connected through hyperedge HE-2 (induced by source paper "adaptive honeypot engagement through reinforcement learning of semi markov decision processes"):
  with members:
    - "a dynamic games approach to proactive defense strategies against advanced persistent threats in cyber physical systems"
    - "adaptive strategic cyber defense for advanced persistent threats in critical infrastructure networks"
    - "modeling and analysis of leaky deception using signaling games with evidence"
    - "distributed and optimal resilient planning of large scale interdependent critical infrastructures"
    - "proactive defense against physical denial of service attacks using poisson signaling games"
    - "optimal timing in dynamic and robust attacker engagement during advanced persistent threats"
    - "a game theoretic taxonomy and survey of defensive deception for cybersecurity and privacy"
    - "a stackelberg game perspective on the conflict between machine learning and data obfuscation"

Connected through hyperedge HE-3 (induced by source paper "game theoretic analysis of cyber deception evidence based strategies and dynamic risk mitigation"):
  with members:
    - "adaptive strategic cyber defense for advanced persistent threats in critical infrastructure networks"
    - "a game theoretic foundation of deception knowledge acquisition and fundamental limits"
    - "proactive defense against physical denial of service attacks using poisson signaling games"
    - "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"
    - "a stackelberg game perspective on the conflict between machine learning and data obfuscation"
    - "deception by design evidence based signaling games for network defense"

Connected through hyperedge HE-4 (induced by source paper "cyber insurance"):
  with members:
    - "modeling and analysis of leaky deception using signaling games with evidence"
    - "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"
    - "a stackelberg game perspective on the conflict between machine learning and data obfuscation"
    - "deception by design evidence based signaling games for network defense"
    - "large scale complex it systems"
    - "a local mean field analysis of security investments in networks"

Connected through hyperedge HE-5 (induced by source paper "game theory meets network security a tutorial"):
  with members:
    - "adaptive strategic cyber defense for advanced persistent threats in critical infrastructure networks"
    - "modeling and analysis of leaky deception using signaling games with evidence"
    - "proactive defense against physical denial of service attacks using poisson signaling games"
    - "a dynamic game analysis and design of infrastructure network protection and recovery 125"
    - "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"
    - "heterogeneous learning in zero sum stochastic games with incomplete information"

Connected through hyperedge HE-6 (induced by source paper "a game theoretic taxonomy and survey of defensive deception for cybersecurity and privacy"):
  with members:
    - "modeling and analysis of leaky deception using signaling games with evidence"
    - "quantitative models of imperfect deception in network security using signaling games with evidence"
    - "information leakage games"
    - "a stackelberg game perspective on the conflict between machine learning and data obfuscation"
    - "deception by design evidence based signaling games for network defense"
    - "privacy games optimal user centric data obfuscation"
    - "flip the cloud cyber physical signaling games in the presence of advanced persistent threats"
    - "a game theoretic study on non monetary incentives in data analytics projects with privacy implications"

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)