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 "detection of advanced malware by machine learning techniques"):
  Abstract: In today’s digital world most of the anti-malware tools are signature based, which is ineffective to detect advanced unknown malware, viz. metamorphic malware. In this paper, we study the frequency of opcode occurrence to detect unknown malware by using machine learning technique. For the purpose, we have used kaggle Microsoft malware classification challenge dataset. The top 20 features obtained from Fisher score, information gain, gain ratio, Chi-square and symmetric uncertainty feature selection methods are compared. We also studied multiple classifiers available in WEKA GUI-based machine learning tool and found that five of them (Random Forest, LMT, NBT, J48 Graft and REPTree) detect the malware with almost 100% accuracy.

Includes members:
  Member "grouping the executables to detect malware with high accuracy":
    also connected through other hyperedges:
      (none)
  Member "an effective approach for classification of advanced malware with high accuracy":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "a survey on the detection of android malicious apps")
  Member "novel feature extraction selection and fusion for effective malware family classification":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "learning from context exploiting and interpreting file path information for better malware 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)