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 "iot keeper securing iot communications in edge networks"):
  Abstract: The increased popularity of IoT devices have made them lucrative targets for attackers. Due to insecure product development practices, these devices are often vulnerable even to very trivial attacks and can be easily compromised. Due to the sheer number and heterogeneity of IoT devices, it is not possible to secure the IoT ecosystem using traditional endpoint and network security solutions. To address the challenges and requirements of securing IoT devices in edge networks, we present IoT-Keeper, which is a novel system capable of securing the network against any malicious activity, in real time. The proposed system uses a lightweight anomaly detection technique, to secure both device-to-device and device-to-infrastructure communications, while using limited resources available on the gateway. It uses unlabeled network data to distinguish between benign and malicious traffic patterns observed in the network. A detailed evaluation, done with real world testbed, shows that IoT-Keeper detects any device generating malicious traffic with high accuracy (0.982) and low false positive rate (0.01). The results demonstrate that IoT-Keeper is lightweight, responsive and can effectively handle complex D2D interactions without requiring explicit attack signatures or sophisticated hardware.

Includes members:
  Member "sequence aggregation rules for anomaly detection in computer network traffic":
    also connected through other hyperedges:
      (none)
  Member "kitsune an ensemble of autoencoders for online network intrusion detection":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "text a 3 activation anomaly analysis")
  Member "one class collective anomaly detection based on long short term memory recurrent neural networks":
    also connected through other hyperedges:
      (none)
  Member "spying on the smart home privacy attacks and defenses on encrypted iot traffic":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "et tu alexa when commodity wifi devices turn into adversarial motion sensors")
  Member "adversarial learning a critical review and active learning study":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "adversarial learning in statistical classification a comprehensive review of defenses against attacks")
  Member "collective anomaly detection based on long short term memory recurrent neural network":
    also connected through other hyperedges:
      (none)
  Member "detection of early stage enterprise infection by mining large scale log data":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "attacking graph based classification via manipulating the graph structure")

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)