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 "measuring abuse in web push advertising"):
  Abstract: The rapid growth of online advertising has fueled the growth of ad-blocking software, such as new ad-blocking and privacy-oriented browsers or browser extensions. In response, both ad publishers and ad networks are constantly trying to pursue new strategies to keep up their revenues. To this end, ad networks have started to leverage the Web Push technology enabled by modern web browsers. #R##N#As web push notifications (WPNs) are relatively new, their role in ad delivery has not been yet studied in depth. Furthermore, it is unclear to what extent WPN ads are being abused for malvertising (i.e., to deliver malicious ads). In this paper, we aim to fill this gap. Specifically, we propose a system called PushAdMiner that is dedicated to (1) automatically registering for and collecting a large number of web-based push notifications from publisher websites, (2) finding WPN-based ads among these notifications, and (3) discovering malicious WPN-based ad campaigns. #R##N#Using PushAdMiner, we collected and analyzed 21,541 WPN messages by visiting thousands of different websites. Among these, our system identified 572 WPN ad campaigns, for a total of 5,143 WPN-based ads that were pushed by a variety of ad networks. Furthermore, we found that 51% of all WPN ads we collected are malicious, and that traditional ad-blockers and malicious URL filters are remarkably ineffective against WPN-based malicious ads, leaving a significant abuse vector unchecked.

Includes members:
  Member "master of web puppets abusing web browsers for persistent and stealthy computation":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "the risks of webgl analysis evaluation and detection")
  Member "who filters the filters understanding the growth usefulness and efficiency of crowdsourced ad blocking":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "keeping out the masses understanding the popularity and implications of internet paywalls")
  Member "tracing information flows between ad exchanges using retargeted ads":
    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 "ad blocking a study on performance privacy and counter measures":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "adperf characterizing the performance of third party ads")
  Member "dial one for scam a large scale analysis of technical support scams":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "large scale analysis of pop up scam on typosquatting urls")
  Member "adscape harvesting and analyzing online display ads":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "towards understanding the information ecosystem through the lens of multiple web communities")

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)