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 "protecting voice controlled systems using sound source identification based on acoustic cues"):
  Abstract: Over the last few years, a rapidly increasing number of Internet-of-Things (IoT) systems that adopt voice as the primary user input have emerged. These systems have been shown to be vulnerable to various types of voice spoofing attacks. Existing defense techniques can usually only protect from a specific type of attack or require an additional authentication step that involves another device. Such defense strategies are either not strong enough or lower the usability of the system. Based on the fact that legitimate voice commands should only come from humans rather than a playback device, we propose a novel defense strategy that is able to detect the sound source of a voice command based on its acoustic features. The proposed defense strategy does not require any information other than the voice command itself and can protect a system from multiple types of spoofing attacks. Our proof-of- concept experiments verify the feasibility and effectiveness of this defense strategy.

Includes members:
  Member "did you hear that adversarial examples against automatic speech recognition":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "towards query efficient black box adversary with zeroth order natural gradient descent")
  Member "audio adversarial examples targeted attacks on speech to text":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "advbox a toolbox to generate adversarial examples that fool neural networks")
  Member "an overview of vulnerabilities of voice controlled systems":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "detecting replay attacks using multi channel audio a neural network based method")
  Member "continuous authentication for voice assistants":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "short range audio channels security survey of mechanisms applications and research challenges")
  Member "dolphinattack inaudible voice commands":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "ghostimage perception domain attacks against vision based object classification systems")
  Member "the insecurity of home digital voice assistants amazon alexa as a case study":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "detecting replay attacks using multi channel audio a neural network based method")
  Member "a study on replay attack and anti spoofing for automatic speaker verification":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "detecting replay attacks using multi channel audio a neural network based method")
  Member "crafting adversarial examples for speech paralinguistics applications":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "identifying audio adversarial examples via anomalous pattern detection")

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)