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 "inferring tracker advertiser relationships in the online advertising ecosystem using header bidding"):
  Abstract: Online advertising relies on trackers and data brokers to show targeted ads to users. To improve targeting, different entities in the intricately interwoven online advertising and tracking ecosystems are incentivized to share information with each other through client-side or server-side mechanisms. Inferring data sharing between entities, especially when it happens at the server-side, is an important and challenging research problem. In this paper, we introduce KASHF: a novel method to infer data sharing relationships between advertisers and trackers by studying how an advertiser's bidding behavior changes as we manipulate the presence of trackers. We operationalize this insight by training an interpretable machine learning model that uses the presence of trackers as features to predict the bidding behavior of an advertiser. By analyzing the machine learning model, we are able to infer relationships between advertisers and trackers irrespective of whether data sharing occurs at the client-side or the server-side. We are also able to identify several server-side data sharing relationships that are validated externally but are not detected by client-side cookie syncing.

Includes members:
  Member "tracking the pixels detecting web trackers via analyzing invisible pixels":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "investigating the effectiveness of web adblockers")
  Member "cookie synchronization everything you always wanted to know but were afraid to ask":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "stop tracking me bro differential tracking of user demographics on hyper partisan websites")
  Member "no more chasing waterfalls a measurement study of the header bidding ad ecosystem":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "stop tracking me bro differential tracking of user demographics on hyper partisan websites")
  Member "tracing information flows between ad exchanges using retargeted ads":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "stop tracking me bro differential tracking of user demographics on hyper partisan websites")
  Member "tracking the trackers towards understanding the mobile advertising and tracking ecosystem":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "keeping out the masses understanding the popularity and implications of internet paywalls")
  Member "your browsing behavior for a big mac economics of personal information online":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "no more chasing waterfalls a measurement study of the header bidding ad ecosystem")

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.CY(Computers and Society)