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: "risk mitigation for dynamic state estimation against cyber attacks and unknown inputs"
  Abstract: Phasor measurement units (PMUs) can be effectively utilized for the monitoring and control of the power grid. As the cyber-world becomes increasingly embedded into power grids, the risks of this inevitable evolution become serious. In this paper, we present a risk mitigation strategy, based on dynamic state estimation, to eliminate threat levels from the grid's unknown inputs and potential cyber-attacks. The strategy requires (a) the potentially incomplete knowledge of power system models and parameters and (b) real-time PMU measurements. #R##N#First, we utilize a dynamic state estimator for higher order depictions of power system dynamics for simultaneous state and unknown inputs estimation. Second, estimates of cyber-attacks are obtained through an attack detection algorithm. Third, the estimation and detection components are seamlessly utilized in an optimization framework to determine the most impacted PMU measurements. Finally, a risk mitigation strategy is proposed to guarantee the elimination of threats from attacks, ensuring the observability of the power system through available, safe measurements. Case studies are included to validate the proposed approach. Insightful suggestions, extensions, and open problems are also posed.

Connected through hyperedge HE-1 (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-2 (induced by source paper "vulnerability analysis of smart grids to gps spoofing"):
  with members:
    - "identification of successive unobservable cyber data attacks in power systems through matrix decomposition"
    - "secure state estimation for nonlinear power systems under cyber attacks"
    - "vulnerability analysis and consequences of false data injection attack on power system state estimation"

Connected through hyperedge HE-3 (induced by source paper "characterizing the nonlinearity of power system generator models"):
  with members:
    - "decentralized robust control for damping inter area oscillations in power systems"

Connected through hyperedge HE-4 (induced by source paper "comparing kalman filters and observers for dynamic state estimation with model uncertainty and malicious cyber attacks"):
  with members:
    - "nonlinear model reduction in power systems by balancing of empirical controllability and observability covariances"

Connected through hyperedge HE-5 (induced by source paper "optimization algorithms for catching data manipulators in power system estimation loops"):
  with members:
    - "distributed inference in the presence of eavesdroppers a survey"

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.SY(Systems and Control)