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 "the audio auditor participant level membership inference in internet of things voice services"):
  Abstract: Voice interfaces and assistants implemented by various services have become increasingly sophisticated, powered by increased availability of data. However, users' audio data needs to be guarded while enforcing data-protection regulations, such as the GDPR law and the COPPA law. To check the unauthorized use of audio data, we propose an audio auditor for users to audit speech recognition models. Specifically, users can check whether their audio recordings were used as a member of the model's training dataset or not. In this paper, we focus our work on a DNN-HMM-based automatic speech recognition model over the TIMIT audio data. As a proof-of-concept, the success rate of participant-level membership inference can reach up to 90\% with eight audio samples per user, resulting in an audio auditor.

Includes members:
  Member "the natural auditor how to tell if someone used your words to train their model":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "dynamic backdoor attacks against machine learning models")
  Member "adversarial attacks against automatic speech recognition systems via psychoacoustic hiding":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "data and model dependencies of membership inference attack")
  Member "stealing hyperparameters in machine learning":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "dynamic backdoor attacks against machine learning models")
  Member "multi task label embedding for text classification":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "hierarchically refined label attention network for sequence labeling")
  Member "stealing machine learning models via prediction apis":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "dynamic backdoor attacks against machine learning models")
  Member "membership inference attacks against machine learning models":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "the future of digital health with federated learning")
  Member "deep speech scaling up end to end speech recognition":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "flexibo cost aware multi objective optimization of deep neural networks")

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)