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: "data injection attacks on smart grids with multiple adversaries a game theoretic perspective"
  Abstract: Data injection attacks have recently emerged as a significant threat on the smart power grid. By launching data injection attacks, an adversary can manipulate the real-time locational marginal prices to obtain economic benefits. Despite the surge of existing literature on data injection, most such works assume the presence of a single attacker and assume no cost for attack or defense. In contrast, in this paper, a model for data injection attacks with multiple adversaries and a single smart grid defender is introduced. To study the defender-attackers interaction, two game models are considered. In the first, a Stackelberg game model is used in which the defender acts as a leader that can anticipate the actions of the adversaries, that act as followers, before deciding on which measurements to protect. The existence and properties of the Stackelberg equilibrium of this game are studied. To find the equilibrium, a distributed learning algorithm that operates under limited system information is proposed and shown to converge to the game solution. In the second proposed game model, it is considered that the defender cannot anticipate the actions of the adversaries. To this end, we proposed a hybrid satisfaction equilibrium - Nash equilibrium game and defined its equilibrium concept. A search algorithm is also provided to find the equilibrium of the hybrid game. Numerical results using the IEEE 30-bus system are used to illustrate and analyze the strategic interactions between the attackers and defender. Our results show that by defending a very small set of measurements, the grid operator can achieve an equilibrium through which the optimal attacks have no effect on the system. Moreover, our results show how, at equilibrium, multiple attackers can play a destructive role towards each other, by choosing to carry out attacks that cancel each other out, leaving the system unaffected.

Connected through hyperedge HE-1 (induced by source paper "game theory for multi access edge computing survey use cases and future trends"):
  with members:
    - "non cooperative game theory based rate adaptation for dynamic video streaming over http"
    - "fog computing a taxonomy survey and future directions"
    - "optimal pricing for a peer to peer sharing platform under network externalities"
    - "a survey on mobile edge networks convergence of computing caching and communications"
    - "a survey on mobile edge computing the communication perspective"
    - "sustainable incentives for mobile crowdsensing"
    - "multi agent reinforcement learning in sequential social dilemmas"
    - "mobile edge computing a survey on architecture and computation offloading"

Connected through hyperedge HE-2 (induced by source paper "state of the art of cyber physical systems security an automatic control perspective"):
  with members:
    - "on redundant observability from security index to attack detection and resilient state estimation"
    - "detection of sensor attack and resilient state estimation for uniformly observable nonlinear systems having redundant sensors"
    - "analysis of stochastic switched systems with application to networked control under jamming attacks"
    - "coding schemes for securing cyber physical systems against stealthy data injection attacks"
    - "detecting integrity attacks on control systems using a moving target approach"
    - "a moving horizon hybrid stochastic game for secure control of cyber physical systems"
    - "modeling and performance evaluation of stealthy false data injection attacks on smart grid in the presence of corrupted measurements"
    - "state estimation with secrecy against eavesdroppers"

Connected through hyperedge HE-3 (induced by source paper "a system level behavioral detection framework for compromised cps devices smart grid case"):
  with members:
    - "real time analysis of privacy un aware iot applications"
    - "aegis a context aware security framework for smart home systems"
    - "sensitive information tracking in commodity iot"
    - "detection of compromised smart grid devices with machine learning and convolution techniques"
    - "advertising in the iot era vision and challenges"
    - "iotdots a digital forensics framework for smart environments"
    - "learning from mutants using code mutation to learn and monitor invariants of a cyber physical system"
    - "machine learning methods for attack detection in the smart grid"

Connected through hyperedge HE-4 (induced by source paper "performance and resilience of cyber physical control systems with reactive attack mitigation"):
  with members:
    - "optimal attack against cyber physical control systems with reactive attack mitigation"
    - "design and stability of load side primary frequency control in power systems"
    - "bad data injection attack and defense in electricity market using game theory study"
    - "playing atari with deep reinforcement learning"

Connected through hyperedge HE-5 (induced by source paper "moving target defense for detecting coordinated cyber physical attacks in power grids"):
  with members:
    - "bad data injection attack and defense in electricity market using game theory study"

Connected through hyperedge HE-6 (induced by source paper "deep learning for signal authentication and security in massive internet of things systems"):
  with members:
    - "interference management for cellular connected uavs a deep reinforcement learning approach"
    - "fast uplink grant for machine type communications challenges and opportunities"
    - "deep learning for reliable mobile edge analytics in intelligent transportation systems"
    - "deep learning based dynamic watermarking for secure signal authentication in the internet of things"
    - "cognitive hierarchy theory for distributed resource allocation in the internet of things"
    - "artificial neural networks based machine learning for wireless networks a tutorial"
    - "colonel blotto game for secure state estimation in interdependent critical infrastructure"
    - "proactive resource management in lte u systems a deep learning perspective"

Connected through hyperedge HE-7 (induced by source paper "graph theoretic framework for unified analysis of observability and data injection attacks in the smart grid"):
  with members:
    - "game theory for secure critical interdependent gas power water infrastructure"
    - "prospect theory for enhanced smart grid resilience using distributed energy storage"
    - "on bounded rationality in cyber physical systems security game theoretic analysis with application to smart grid protection"
    - "computing critical k tuples in power networks"
    - "algorithms for implicit hitting set problems"

Connected through hyperedge HE-8 (induced by source paper "survey of game theory and future trends with application to emerging wireless data communication networks"):
  with members:
    - "non cooperative game theory based rate adaptation for dynamic video streaming over http"
    - "fog computing a taxonomy survey and future directions"
    - "a survey on mobile edge computing the communication perspective"
    - "sustainable incentives for mobile crowdsensing"
    - "mobile edge computing a survey on architecture and computation offloading"
    - "game theory models for communication between agents a review"
    - "game theoretic multi agent control and network cost allocation under communication constraints"
    - "a survey on applications of model free strategy learning in cognitive wireless networks"

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)