human: Given a node-centered hypergraph: <hypergraph>, where nodes represent papers and hyperedges represent sets of papers co-cited by a source paper.

Details of the hypergraph:
Center node: "tracking the pixels detecting web trackers via analyzing invisible pixels"
  Abstract: Web tracking has been extensively studied over the last decade. To detect tracking, most of the research studies and user tools rely on consumer protection lists. However, there was always a suspicion that lists miss unknown trackers. In this paper, we propose an alternative solution to detect trackers by analyzing behavior of invisible pixels that are perfect suspects for tracking. By crawling 829,349 webpages, we detect that third-party invisible pixels are widely deployed: they are present on more than 83% of domains and constitute 37.22% of all third-party images. We then propose a fine-grained classification of tracking based on the analysis of invisible pixels and use this classification to detect new categories of tracking and uncover new collaborations between domains on the full dataset of 34,952,217 third-party requests. We demonstrate that two blocking strategies – based on EasyList&EasyPrivacy and on Disconnect lists – each miss 22% of the trackers that we detect. Moreover, we find that if we combine both strategies, 238,439 requests (11%) originated from 7,773 domains that still track users on 5,098 websites.

Connected through hyperedge HE-1 (induced by source paper "investigating the effectiveness of web adblockers"):
  with members:
    - "adversarial perceptual ad blocking meets adversarial machine learning"
    - "who filters the filters understanding the growth usefulness and efficiency of crowdsourced ad blocking"
    - "the future of ad blocking an analytical framework and new techniques"
    - "ad blocking a study on performance privacy and counter measures"
    - "a first look at ad block detection a new arms race on the web"

Connected through hyperedge HE-2 (induced by source paper "inferring tracker advertiser relationships in the online advertising ecosystem using header bidding"):
  with members:
    - "cookie synchronization everything you always wanted to know but were afraid to ask"
    - "no more chasing waterfalls a measurement study of the header bidding ad ecosystem"
    - "tracing information flows between ad exchanges using retargeted ads"
    - "tracking the trackers towards understanding the mobile advertising and tracking ecosystem"
    - "your browsing behavior for a big mac economics of personal information online"

Connected through hyperedge HE-3 (induced by source paper "who s tracking sensitive domains"):
  with members:
    - "cookie synchronization everything you always wanted to know but were afraid to ask"
    - "tracing information flows between ad exchanges using retargeted ads"
    - "demo recon revealing and controlling pii leaks in mobile network traffic"
    - "variations in tracking in relation to geographic location"

Question: Please tell me which class the center node 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)