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: "efficient cyber attacks detection in industrial control systems using lightweight neural networks"
  Abstract: Industrial control systems (ICSs) are widely used and vital to industry and society. Their failure can have severe impact on both economics and human life. Hence, these systems have become an attractive target for attacks, both physical and cyber. A number of attacks detection methods were proposed, however, they are characterized by an insufficient detection rate, a substantial false positives rate, or are system specific. In this paper, we study an attack detection method based on simple and lightweight neural networks, namely, 1D convolutions and autoencoders. We apply these networks to both time and frequency domains of the collected data and discuss pros and cons of each approach. We evaluate the suggested method on three popular public datasets and achieve detection metrics matching or exceeding previously published detection results, while featuring small footprint, short training and detection times, and generality.

Connected through hyperedge HE-1 (induced by source paper "can t boil this frog robustness of online trained autoencoder based anomaly detectors to adversarial poisoning attacks"):
  with members:
    - "real time evasion attacks with physical constraints on deep learning based anomaly detectors in industrial control systems"
    - "deep learning for anomaly detection a survey"
    - "intrusion detection for industrial control systems evaluation analysis and adversarial attacks"
    - "manipulating machine learning poisoning attacks and countermeasures for regression learning"
    - "poison frogs targeted clean label poisoning attacks on neural networks"
    - "adversarial regression for detecting attacks in cyber physical systems"
    - "a deep learning based framework for conducting stealthy attacks in industrial control systems"
    - "cyber physical systems security a survey"

Connected through hyperedge HE-2 (induced by source paper "intrusion detection for industrial control systems evaluation analysis and adversarial attacks"):
  with members:
    - "deep latent defence"
    - "real time evasion attacks with physical constraints on deep learning based anomaly detectors in industrial control systems"
    - "mad gan multivariate anomaly detection for time series data with generative adversarial networks"
    - "adversarial patch"
    - "anomaly detection for water treatment system based on neural network with automatic architecture optimization"
    - "deep k nearest neighbors towards confident interpretable and robust deep learning"
    - "early stage malware prediction using recurrent neural networks"
    - "audio adversarial examples targeted attacks on speech to text"

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)