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: "subspace methods for data attack on state estimation a data driven approach"
  Abstract: Data attacks on state estimation modify part of system measurements such that the tempered measurements cause incorrect system state estimates. Attack techniques proposed in the literature often require detailed knowledge of system parameters. Such information is difficult to acquire in practice. The subspace methods presented in this paper, on the other hand, learn the system operating subspace from measurements and launch attacks accordingly. Conditions for the existence of an unobservable subspace attack are obtained under the full and partial measurement models. Using the estimated system subspace, two attack strategies are presented. The first strategy aims to affect the system state directly by hiding the attack vector in the system subspace. The second strategy misleads the bad data detection mechanism so that data not under attack are removed. Performance of these attacks are evaluated using the IEEE 14-bus network and the IEEE 118-bus network.

Connected through hyperedge HE-1 (induced by source paper "data driven false data injection attacks against power grid a random matrix approach"):
  with members:
    - "sparse attack construction and state estimation in the smart grid centralized and distributed models"

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 "protecting the grid against iot botnets of high wattage devices"):
  with members:
    - "iot enabled distributed cyber attacks on transmission and distribution grids"

Connected through hyperedge HE-4 (induced by source paper "modeling and performance evaluation of stealthy false data injection attacks on smart grid in the presence of corrupted measurements"):
  with members:
    - "data framing attack on state estimation"
    - "vulnerabilities of smart grid state estimation against false data injection attack"
    - "sparse attack construction and state estimation in the smart grid centralized and distributed models"
    - "robust principal component analysis"

Connected through hyperedge HE-5 (induced by source paper "react to cyber attacks on power grids"):
  with members:
    - "expose the line failures following a cyber physical attack on the power grid"
    - "power grid vulnerability to geographically correlated failures analysis and control 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)