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 "celeb df a new dataset for deepfake forensics"):
  Abstract: AI-synthesized face swapping videos, commonly known as the DeepFakes, have become an emerging problem recently. Correspondingly, there is an increasing interest in developing algorithms that can detect them. However, existing dataset of DeepFake videos suffer from low visual quality and abundant artifacts that do not reflect the reality of DeepFake videos circulated on the Internet. In this work, we present a new DeepFake dataset, Celeb-DF, for the development and evaluation of DeepFake detection algorithms. The Celeb-DF dataset is generated using a refined synthesis algorithm that reduces the visual artifacts observed in existing datasets. Based on the Celeb-DF dataset, we also benchmark existing DeepFake detection algorithms.

Includes members:
  Member "multi task learning for detecting and segmenting manipulated facial images and videos":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "deepfakes and beyond a survey of face manipulation and fake detection")
  Member "faceforensics learning to detect manipulated facial images":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "watch your up convolution cnn based generative deep neural networks are failing to reproduce spectral distributions")
  Member "recurrent convolutional strategies for face manipulation detection in videos":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "deepfakes and beyond a survey of face manipulation and fake detection")
  Member "the deepfake detection challenge dfdc preview dataset":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "deepfakes and beyond a survey of face manipulation and fake detection")
  Member "hybrid lstm and encoder decoder architecture for detection of image forgeries":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "celeb df a large scale challenging dataset for deepfake forensics")
  Member "use of a capsule network to detect fake images and videos":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "celeb df a large scale challenging dataset for deepfake forensics")
  Member "learning rich features for image manipulation detection":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "deepfakes and beyond a survey of face manipulation and fake detection")
  Member "exposing deep fakes using inconsistent head poses":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "deepfakes and beyond a survey of face manipulation and fake 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)