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 "tiny noise can make an eeg based brain computer interface speller output anything"):
  Abstract: An electroencephalogram (EEG) based brain-computer interface (BCI) speller allows a user to input text to a computer by thought. It is particularly useful to severely disabled individuals, e.g., amyotrophic lateral sclerosis patients, who have no other effective means of communication with another person or a computer. Most studies so far focused on making EEG-based BCI spellers faster and more reliable; however, few have considered their security. Here we show that P300 and steady-state visual evoked potential BCI spellers are very vulnerable, i.e., they can be severely attacked by adversarial perturbations, which are too tiny to be noticed when added to EEG signals, but can mislead the spellers to spell anything the attacker wants. The consequence could range from merely user frustration to severe misdiagnosis in clinical applications. We hope our research can attract more attention to the security of EEG-based BCI spellers, and more broadly, EEG-based BCIs, which has received little attention before.

Includes members:
  Member "on the vulnerability of cnn classifiers in eeg based bcis":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "universal adversarial perturbations for cnn classifiers in eeg based bcis")
  Member "adversarial patch":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "sentinet detecting localized universal attacks against deep learning systems")
  Member "audio adversarial examples targeted attacks on speech to text":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "advbox a toolbox to generate adversarial examples that fool neural networks")
  Member "adversarial examples for evaluating reading comprehension systems":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "a study of the tasks and models in machine reading comprehension")
  Member "adversarial perturbations against deep neural networks for malware classification":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "on the security of randomized defenses against adversarial samples")
  Member "transferability in machine learning from phenomena to black box attacks using adversarial samples":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "adversarial ranking attack and defense")
  Member "universal adversarial perturbations":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "adversarial ranking attack and defense")
  Member "delving into transferable adversarial examples and black box attacks":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "adversarial ranking attack and defense")

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.HC(Human-Computer Interaction)