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 "modern problems require modern solutions hybrid concepts for industrial intrusion detection"):
  Abstract: The concept of Industry 4.0 brings a disruption into the processing industry. It is characterised by a high degree of intercommunication, embedded computation, resulting in a decentralised and distributed handling of data. Additionally, cloud-storage and Software-as-a-Service (SaaS) approaches enhance a centralised storage and handling of data. This often takes place in third-party networks. Furthermore, Industry 4.0 is driven by novel business cases. Lot sizes of one, customer individual production, observation of process state and progress in real-time and remote maintenance, just to name a few. All of these new business cases make use of the novel technologies. However, cyber security has not been an issue in industry. Industrial networks have been considered physically separated from public networks. Additionally, the high level of uniqueness of any industrial network was said to prevent attackers from exploiting flaws. Those assumptions are inherently broken by the concept of Industry 4.0. As a result, an abundance of attack vectors is created. In the past, attackers have used those attack vectors in spectacular fashions. Especially Small and Mediumsized Enterprises (SMEs) in Germany struggle to adapt to these challenges. Reasons are the cost required for technical solutions and security professionals. In order to enable SMEs to cope with the growing threat in the cyberspace, the research project IUNO Insec aims at providing and improving security solutions that can be used without specialised security knowledge. The project IUNO Insec is briefly introduced in this work. Furthermore, contributions in the field of intrusion detection, especially machine learning-based solutions, for industrial environments provided by the authors are presented and set into context.

Includes members:
  Member "devil in the detail attack scenarios in industrial applications":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "discussing the feasibility of acoustic sensors for side channel aided industrial intrusion detection an essay")
  Member "highly scalable and flexible model for effective aggregation of context based data in generic iiot scenarios":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "using temporal and topological features for intrusion detection in operational networks")
  Member "implementing scada scenarios and introducing attacks to obtain training data for intrusion detection methods":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "discussing the feasibility of acoustic sensors for side channel aided industrial intrusion detection an essay")
  Member "evaluation of machine learning based anomaly detection algorithms on an industrial modbus tcp data set":
    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 "time is of the essence machine learning based intrusion detection in industrial time series data":
    also connected through other hyperedges:
      - Hyperedge HE-5 (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-6 (induced by source paper "devil in the detail attack scenarios in industrial applications")
  Member "two decades of scada exploitation a brief history":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "discussing the feasibility of acoustic sensors for side channel aided industrial intrusion detection an essay")

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.CR(Cryptography and Security)