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 "recent advances of image steganography with generative adversarial networks"):
  Abstract: In the past few years, the Generative Adversarial Network (GAN) which proposed in 2014 has achieved great success. GAN has achieved many research results in the field of computer vision and natural language processing. Image steganography is dedicated to hiding secret messages in digital images, and has achieved the purpose of covert communication. Recently, research on image steganography has demonstrated great potential for using GAN and neural networks. In this paper we review different strategies for steganography such as cover modification, cover selection and cover synthesis by GANs, and discuss the characteristics of these methods as well as evaluation metrics and provide some possible future research directions in image steganography.

Includes members:
  Member "steganogan high capacity image steganography with gans":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "distortion agnostic deep watermarking")
  Member "cnn based adversarial embedding for image steganography":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "neural imaging pipelines the scourge or hope of forensics")
  Member "stegastamp invisible hyperlinks in physical photographs":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "distortion agnostic deep watermarking")
  Member "deep learning in steganography and steganalysis from 2015 to 2018":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "steganography using a 3 player game")
  Member "spatial image steganography based on generative adversarial network":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "pixelsteganalysis destroying hidden information with a low degree of visual degradation")
  Member "adaptive spatial steganography based on probability controlled adversarial examples":
    also connected through other hyperedges:
      (none)
  Member "generative adversarial networks an overview":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "generative adversarial networks in computer vision a survey and taxonomy")
  Member "an introduction to image synthesis with generative adversarial nets":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "reshapegan object reshaping by providing a single reference image")

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)