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 "uncovering download fraud activities in mobile app markets"):
  Abstract: Download fraud is a prevalent threat in mobile App markets, where fraudsters manipulate the number of downloads of Apps via various cheating approaches. Purchased fake downloads can mislead recommendation and search algorithms and further lead to bad user experience in App markets. In this paper, we investigate download fraud problem based on a company's App Market, which is one of the most popular Android App markets. We release a honeypot App on the App Market and purchase fake downloads from fraudster agents to track fraud activities in the wild. Based on our interaction with the fraudsters, we categorize download fraud activities into three types according to their intentions: boosting front end downloads, optimizing App search ranking, and enhancing user acquisition&retention rate. For the download fraud aimed at optimizing App search ranking, we select, evaluate, and validate several features in identifying fake downloads based on billions of download data. To get a comprehensive understanding of download fraud, we further gather stances of App marketers, fraudster agencies, and market operators on download fraud. The followed analysis and suggestions shed light on the ways to mitigate download fraud in App markets and other social platforms. To the best of our knowledge, this is the first work that investigates the download fraud problem in mobile App markets.

Includes members:
  Member "beyond google play a large scale comparative study of chinese android app markets":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "characterizing cryptocurrency exchange scams")
  Member "smoke screener or straight shooter detecting elite sybil attacks in user review social networks":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "scalable explanation of inferences on large graphs")
  Member "the paradigm shift of social spambots evidence theories and tools for the arms race":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "how many bots are you following")
  Member "fairplay fraud and malware detection in google play":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "search rank fraud de anonymization in online systems")
  Member "xgboost a scalable tree boosting system":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "monotonic cardinality estimation of similarity selection a deep learning approach")
  Member "the dark side of micro task marketplaces characterizing fiverr and automatically detecting crowdturfing":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "generating sentiment preserving fake online reviews using neural language models and their human and machine based detection")
  Member "paying for likes understanding facebook like fraud using honeypots":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "the art of social bots a review and a refined taxonomy")
  Member "serf and turf crowdturfing for fun and profit":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "text analysis in adversarial settings does deception leave a stylistic trace")

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)