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: "identification of successive unobservable cyber data attacks in power systems through matrix decomposition"
  Abstract: This paper presents a new framework of identifying a series of cyber data attacks on power system synchrophasor measurements. We focus on detecting “unobservable” cyber data attacks that cannot be detected by any existing method that purely relies on measurements received at one time instant. Leveraging the approximate low-rank property of phasor measurement unit (PMU) data, we formulate the identification problem of successive unobservable cyber attacks as a matrix decomposition problem of a low-rank matrix plus a transformed column-sparse matrix. We propose a convex-optimization-based method and provide its theoretical guarantee in the data identification. Numerical experiments on actual PMU data from the Central New York power system and synthetic data are conducted to verify the effectiveness of the proposed method.

Connected through hyperedge HE-1 (induced by source paper "vulnerability analysis of smart grids to gps spoofing"):
  with members:
    - "secure state estimation for nonlinear power systems under cyber attacks"
    - "vulnerability analysis and consequences of false data injection attack on power system state estimation"
    - "risk mitigation for dynamic state estimation against cyber attacks and unknown inputs"

Connected through hyperedge HE-2 (induced by source paper "unobservable false data injection attacks against pmus feasible conditions and multiplicative attacks"):
  with members:
    - "can attackers with limited information exploit historical data to mount successful false data injection attacks on power systems"
    - "evaluating power system vulnerability to false data injection attacks via scalable optimization"
    - "vulnerability analysis and consequences of false data injection attack on power system state estimation"

Connected through hyperedge HE-3 (induced by source paper "false data injection attacks on phasor measurements that bypass low rank decomposition"):
  with members:
    - "can attackers with limited information exploit historical data to mount successful false data injection attacks on power systems"
    - "evaluating power system vulnerability to false data injection attacks via scalable optimization"
    - "vulnerability analysis and consequences of false data injection attack on power system state estimation"
    - "robust pca via outlier pursuit"

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.IT(Information Theory)