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: "the insecurity of home digital voice assistants amazon alexa as a case study"
  Abstract: Home Digital Voice Assistants (HDVAs) are getting popular in recent years. Users can control smart devices and get living assistance through those HDVAs (e.g., Amazon Alexa, Google Home) using voice. In this work, we study the insecurity of HDVA service by using Amazon Alexa as a case study. We disclose three security vulnerabilities which root in the insecure access control of Alexa services. We then exploit them to devise two proof-of-concept attacks, home burglary and fake order, where the adversary can remotely command the victim's Alexa device to open a door or place an order from Amazon.com. The insecure access control is that the Alexa device not only relies on a single-factor authentication but also takes voice commands even if no people are around. We thus argue that HDVAs should have another authentication factor, a physical presence based access control; that is, they can accept voice commands only when any person is detected nearby. To this end, we devise a Virtual Security Button (VSButton), which leverages the WiFi technology to detect indoor human motions. Once any indoor human motion is detected, the Alexa device is enabled to accept voice commands. Our evaluation results show that it can effectively differentiate indoor motions from the cases of no motion and outdoor motions in both the laboratory and real world settings.

Connected through hyperedge HE-1 (induced by source paper "detecting replay attacks using multi channel audio a neural network based method"):
  with members:
    - "remasc realistic replay attack corpus for voice controlled systems"
    - "real time adversarial attacks"
    - "protecting voice controlled systems using sound source identification based on acoustic cues"
    - "an overview of vulnerabilities of voice controlled systems"
    - "a study on replay attack and anti spoofing for automatic speaker verification"
    - "decoupled weight decay regularization"
    - "crafting adversarial examples for speech paralinguistics applications"
    - "your voice assistant is mine how to abuse speakers to steal information and control your phone"

Connected through hyperedge HE-2 (induced by source paper "cagfuzz coverage guided adversarial generative fuzzing testing of deep learning systems"):
  with members:
    - "machine learning testing survey landscapes and horizons"
    - "semantic fuzzing with zest"
    - "deepgauge multi granularity testing criteria for deep learning systems"
    - "defense gan protecting classifiers against adversarial attacks using generative models"
    - "software reliability growth models predict autonomous vehicle disengagement events"
    - "deephunter hunting deep neural network defects via coverage guided fuzzing"
    - "dlfuzz differential fuzzing testing of deep learning systems"
    - "testing deep neural networks"

Connected through hyperedge HE-3 (induced by source paper "sirenattack generating adversarial audio for end to end acoustic systems"):
  with members:
    - "commandersong a systematic approach for practical adversarial voice recognition"
    - "audio adversarial examples targeted attacks on speech to text"
    - "continuous authentication for voice assistants"
    - "dolphinattack inaudible voice commands"
    - "dual path networks"
    - "exploring neural transducers for end to end speech recognition"
    - "crafting adversarial examples for speech paralinguistics applications"
    - "knowledge transfer from weakly labeled audio using convolutional neural network for sound events and scenes"

Connected through hyperedge HE-4 (induced by source paper "smart home personal assistants a security and privacy review"):
  with members:
    - "intelligent virtual assistant knows your life"
    - "adversarial attacks against automatic speech recognition systems via psychoacoustic hiding"
    - "contextual slot carryover for disparate schemas"
    - "user perceptions of smart home iot privacy"
    - "understanding and mitigating the security risks of voice controlled third party skills on amazon alexa and google home"
    - "sok security and privacy in machine learning"
    - "audio adversarial examples targeted attacks on speech to text"
    - "comparing speech and keyboard text entry for short messages in two languages on touchscreen phones"

Connected through hyperedge HE-5 (induced by source paper "privacy preserving adversarial representation learning in asr reality or illusion"):
  with members:
    - "espnet end to end speech processing toolkit"
    - "fully convolutional speech recognition"
    - "to reverse the gradient or not an empirical comparison of adversarial and multi task learning in speech recognition"
    - "invariant representations for noisy speech recognition"
    - "musan a music speech and noise corpus"
    - "attention based models for speech recognition"

Connected through hyperedge HE-6 (induced by source paper "beware of the app on the vulnerability surface of smart devices through their companion apps"):
  with members:
    - "program analysis of commodity iot applications for security and privacy challenges and opportunities"
    - "soteria automated iot safety and security analysis"

Connected through hyperedge HE-7 (induced by source paper "protecting voice controlled systems using sound source identification based on acoustic cues"):
  with members:
    - "did you hear that adversarial examples against automatic speech recognition"
    - "audio adversarial examples targeted attacks on speech to text"
    - "an overview of vulnerabilities of voice controlled systems"
    - "continuous authentication for voice assistants"
    - "dolphinattack inaudible voice commands"
    - "a study on replay attack and anti spoofing for automatic speaker verification"
    - "crafting adversarial examples for speech paralinguistics applications"
    - "your voice assistant is mine how to abuse speakers to steal information and control your phone"

Connected through hyperedge HE-8 (induced by source paper "an overview of vulnerabilities of voice controlled systems"):
  with members:
    - "did you hear that adversarial examples against automatic speech recognition"
    - "audio adversarial examples targeted attacks on speech to text"
    - "continuous authentication for voice assistants"
    - "dolphinattack inaudible voice commands"
    - "crafting adversarial examples for speech paralinguistics applications"
    - "towards evaluating the robustness of neural networks"
    - "your voice assistant is mine how to abuse speakers to steal information and control your phone"
    - "deep speech scaling up end to end speech recognition"

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)