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: "cleartext data transmissions in consumer iot medical devices"
  Abstract: This paper introduces a method to capture network traffic from medical IoT devices and automatically detect cleartext information that may reveal sensitive medical conditions and behaviors. The research follows a three-step approach involving traffic collection, cleartext detection, and metadata analysis. We analyze four popular consumer medical IoT devices, including one smart medical device that leaks sensitive health information in cleartext. We also present a traffic capture and analysis system that seamlessly integrates with a home network and offers a user-friendly interface for consumers to monitor and visualize data transmissions of IoT devices in their homes.

Connected through hyperedge HE-1 (induced by source paper "iot behavioral monitoring via network traffic analysis"):
  with members:
    - "machine learning ddos detection for consumer internet of things devices"
    - "peek a boo i see your smart home activities even encrypted"
    - "n baiot network based detection of iot botnet attacks using deep autoencoders"
    - "iot device fingerprint using deep learning"
    - "a smart home is no castle privacy vulnerabilities of encrypted iot traffic"
    - "iot sentinel demo automated device type identification for security enforcement in iot"
    - "idiot securing the internet of things like it s 1994"
    - "amplification and drdos attack defense a survey and new perspectives"

Connected through hyperedge HE-2 (induced by source paper "characterizing smart home iot traffic in the wild"):
  with members:
    - "iot inspector crowdsourcing labeled network traffic from smart home devices at scale"
    - "vpn0 a privacy preserving decentralized virtual private network"
    - "keeping the smart home private with smart er iot traffic shaping"
    - "an analysis of home iot network traffic and behaviour"

Connected through hyperedge HE-3 (induced by source paper "iot inspector crowdsourcing labeled network traffic from smart home devices at scale"):
  with members:
    - "improving heart rate variability measurements from consumer smartwatches with machine learning"
    - "kitsune an ensemble of autoencoders for online network intrusion detection"
    - "playing with danger a taxonomy and evaluation of threats to smart toys"
    - "keeping the smart home private with smart er iot traffic shaping"
    - "security and privacy analyses of internet of things children s toys"
    - "iot sentinel demo automated device type identification for security enforcement in iot"

Connected through hyperedge HE-4 (induced by source paper "hedge efficient traffic classification of encrypted and compressed packets"):
  with members:
    - "detecting compressed cleartext traffic from consumer internet of things devices"
    - "robust smartphone app identification via encrypted network traffic analysis"

Connected through hyperedge HE-5 (induced by source paper "detecting compressed cleartext traffic from consumer internet of things devices"):
  with members:
    - "automatic tagging using deep convolutional neural networks"
    - "adam a method for stochastic optimization"

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)