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 "screenavoider protecting computer screens from ubiquitous cameras"):
  Abstract: We live and work in environments that are inundated with cameras embedded in devices such as phones, tablets, laptops, and monitors. Newer wearable devices like Google Glass, Narrative Clip, and Autographer offer the ability to quietly log our lives with cameras from a `first person' perspective. While capturing several meaningful and interesting moments, a significant number of images captured by these wearable cameras can contain computer screens. Given the potentially sensitive information that is visible on our displays, there is a need to guard computer screens from undesired photography. People need protection against photography of their screens, whether by other people's cameras or their own cameras. #R##N#We present ScreenAvoider, a framework that controls the collection and disclosure of images with computer screens and their sensitive content. ScreenAvoider can detect images with computer screens with high accuracy and can even go so far as to discriminate amongst screen content. We also introduce a ScreenTag system that aids in the identification of screen content, flagging images with highly sensitive content such as messaging applications or email webpages. We evaluate our concept on realistic lifelogging datasets, showing that ScreenAvoider provides a practical and useful solution that can help users manage their privacy.

Includes members:
  Member "return of the devil in the details delving deep into convolutional nets":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "a survey on deep hashing methods")
  Member "imagenet large scale visual recognition challenge":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "using a thousand optimization tasks to learn hyperparameter search strategies")
  Member "placeraider virtual theft in physical spaces with smartphones":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "fully coupled two stream spatiotemporal networks for extremely low resolution action recognition")

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)