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 "time is of the essence machine learning based intrusion detection in industrial time series data"):
  Abstract: The Industrial Internet of Things drastically increases connectivity of devices in industrial applications. In addition to the benefits in efficiency, scalability and ease of use, this creates novel attack surfaces. Historically, industrial networks and protocols do not contain means of security, such as authentication and encryption, that are made necessary by this development. Thus, industrial IT-security is needed. In this work, emulated industrial network data is transformed into a time series and analysed with three different algorithms. The data contains labeled attacks, so the performance can be evaluated. Matrix Profiles perform well with almost no parameterisation needed. Seasonal Autoregressive Integrated Moving Average performs well in the presence of noise, requiring parameterisation effort. Long Short Term Memory-based neural networks perform mediocre while requiring a high training- and parameterisation effort.

Includes members:
  Member "highly scalable and flexible model for effective aggregation of context based data in generic iiot scenarios":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "modern problems require modern solutions hybrid concepts for industrial intrusion detection")
  Member "evaluation of machine learning based anomaly detection algorithms on an industrial modbus tcp data set":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "discussing the feasibility of acoustic sensors for side channel aided industrial intrusion detection an essay")
  Member "a question of context enhancing intrusion detection by providing context information":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "modern problems require modern solutions hybrid concepts for industrial intrusion detection")
  Member "two decades of scada exploitation a brief history":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "discussing the feasibility of acoustic sensors for side channel aided industrial intrusion detection an essay")
  Member "multivariate industrial time series with cyber attack simulation fault detection using an lstm based predictive data model":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "anomaly detection in beehives using deep recurrent autoencoders")

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.LG(Machine Learning)