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 "who filters the filters understanding the growth usefulness and efficiency of crowdsourced ad blocking"):
  Abstract: Ad and tracking blocking extensions are popular tools for improving web performance, privacy and aesthetics. Content blocking extensions typically rely on filter lists to decide whether a web request is associated with tracking or advertising, and so should be blocked. Millions of web users rely on filter lists to protect their privacy and improve their browsing experience. #R##N#Despite their importance, the growth and health of filter lists are poorly understood. Filter lists are maintained by a small number of contributors, who use a variety of undocumented heuristics to determine what rules should be included. Lists quickly accumulate rules, and rules are rarely removed. As a result, users' browsing experiences are degraded as the number of stale, dead or otherwise not useful rules increasingly dwarf the number of useful rules, with no attenuating benefit. An accumulation of "dead weight" rules also makes it difficult to apply filter lists on resource-limited mobile devices. #R##N#This paper improves the understanding of crowdsourced filter lists by studying EasyList, the most popular filter list. We find that EasyList has grown from several hundred rules, to well over 60,000 rules, during its 9-year history. We measure how EasyList affects web browsing by applying EasyList to a sample of 10,000 websites. We find that 90.16% of the resource blocking rules in EasyList provide no benefit to users in common browsing scenarios. We further use our changes in EasyList application rates to provide a taxonomy of the ways advertisers evade EasyList rules. Finally, we propose optimizations for popular ad-blocking tools, that allow EasyList to be applied on performance constrained mobile devices, and improve desktop performance by 62.5%, while preserving over 99% of blocking coverage.

Includes members:
  Member "a long way to the top significance structure and stability of internet top lists":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "must should don t care tcp conformance in the wild")
  Member "the future of ad blocking an analytical framework and new techniques":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "a4 evading learning based adblockers")
  Member "ad blocking a study on performance privacy and counter measures":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "measuring abuse in web push advertising")
  Member "exposing the hidden web an analysis of third party http requests on 1 million websites":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "do cookie banners respect my choice measuring legal compliance of banners from iab europe s transparency and consent framework")

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)