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 "a survey on the detection of android malicious apps"):
  Abstract: Android-based smart devices are exponentially growing, and due to the ubiquity of the Internet, these devices are globally connected to the different devices/networks. Its popularity, attractive features, and mobility make malware creator to put number of malicious apps in the market to disrupt and annoy the victims. Although to identify the malicious apps, time-to-time various techniques are proposed. However, it appears that malware developers are always ahead of the anti-malware group, and the proposed techniques by the anti-malware groups are not sufficient to counter the advanced malicious apps. Therefore, to understand the various techniques proposed/used for the identification of Android malicious apps, in this paper, we present a survey conducted by us on the work done by the researchers in this field.

Includes members:
  Member "group wise classification approach to improve android malicious apps detection accuracy":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "an efficient detection of malware by naive bayes classifier using gpgpu")
  Member "an investigation of the classifiers to detect android malicious apps":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "group wise classification approach to improve android malicious apps detection accuracy")
  Member "an effective approach for classification of advanced malware with high accuracy":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "an efficient detection of malware by naive bayes classifier using gpgpu")
  Member "adaptive and scalable android malware detection through online learning":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "group wise classification approach to improve android malicious apps detection accuracy")
  Member "improving the detection accuracy of unknown malware by partitioning the executables in groups":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "an efficient detection of malware by naive bayes classifier using gpgpu")
  Member "n opcode analysis for android malware classification and categorization":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "dl droid deep learning based android malware detection using real devices")
  Member "evolution and detection of polymorphic and metamorphic malwares a survey":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "an efficient detection of malware by naive bayes classifier using gpgpu")
  Member "droidanalytics a signature based analytic system to collect extract analyze and associate android malware":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "rebooting research on detecting repackaged android apps literature review and benchmark")

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)