human: Given a hyperedge-centered hypergraph: <hypergraph>, where the center hyperedge is induced by one source paper and its member nodes are the cited papers.

Details of the hypergraph:
Center hyperedge (induced by source paper "enhancing power system cyber security with systematic two stage detection strategy"):
  Abstract: State estimation estimates the system condition in real-time and provides a base case for other energy management system (EMS) applications including real-time contingency analysis and security-constrained economic dispatch. Recent work in the literature shows malicious cyber-attack can inject false measurements that bypass traditional bad data detection in state estimation and cause actual overloads. Thus, it is very important to detect such cyber-attack. In this paper, multiple metrics are proposed to monitor abnormal load deviations and suspicious branch flow changes. A systematic two-stage approach is proposed to detect false data injection (FDI) cyber-attack. The first stage determines whether the system is under attack while the second stage identifies the target branch. Numerical simulations verify that FDI can cause severe system violations and demonstrate the effectiveness of the proposed two-stage FDI detection (FDID) method. It is concluded that the proposed FDID approach can efficiently detect FDI cyber-attack and identify the target branch, which will substantially improve operators situation awareness in real-time.

Includes members:
  Member "evaluating power system vulnerability to false data injection attacks via scalable optimization":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "can predictive filters detect gradually ramping false data injection attacks against pmus")
  Member "vulnerability analysis and consequences of false data injection attack on power system state estimation":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "state of the art of cyber physical systems security an automatic control perspective")

Question: Please tell me which class the source paper 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)