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 "an efficient detection of malware by naive bayes classifier using gpgpu"):
  Abstract: Due to continuous increase in the number of malware (according to AV-Test institute total \({\sim } 8 \times 10^8\) malware are already known, and every day they register \({\sim } 2.5 \times 10^4\) malware) and files in the computational devices, it is very important to design a system which not only effectively but can also efficiently detect the new or previously unseen malware to prevent/minimize the damages. Therefore, this paper presents a novel group-wise approach for the efficient detection of malware by parallelizing the classification using the power of GPGPU and shown that by using the Naive Bayes classifier, the detection speedup can be boosted up to 200x. The investigation also shows that the classification time increases significantly with the number of features.

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 "a survey on the detection of android malicious apps")
  Member "adversarial deep learning for robust detection of binary encoded malware":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "effectiveness of adversarial examples and defenses for malware classification")
  Member "microsoft malware classification challenge":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "interpreting machine learning malware detectors which leverage n gram analysis")
  Member "an effective approach for classification of advanced malware with high accuracy":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "a survey on the detection of android malicious apps")
  Member "acceleration of statistical detection of zero day malware in the memory dump using cuda enabled gpu hardware":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "memoryranger prevents hijacking file_object structures in windows kernel")
  Member "improving the detection accuracy of unknown malware by partitioning the executables in groups":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "a survey on the detection of android malicious apps")
  Member "evolution and detection of polymorphic and metamorphic malwares a survey":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "a survey on the detection of android malicious apps")

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)