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: "the price of free illegal live streaming services"
  Abstract: As Internet streaming of live content has gained on traditional cable TV viewership, we have also seen significant growth of free live streaming services which illegally provide free access to copyrighted content over the Internet. Some of these services draw millions of viewers each month. Moreover, this viewership has continued to increase, despite the consistent coupling of this free content with deceptive advertisements and user-hostile tracking. #R##N#In this paper, we explore the ecosystem of free illegal live streaming services by collecting and examining the behavior of a large corpus of illegal sports streaming websites. We explore and quantify evidence of user tracking via third-party HTTP requests, cookies, and fingerprinting techniques on more than $27,303$ unique video streams provided by $467$ unique illegal live streaming domains. We compare the behavior of illegal live streaming services with legitimate services and find that the illegal services go to much greater lengths to track users than most legitimate services, and use more obscure tracking services. Similarly, we find that moderated sites that aggregate links to illegal live streaming content fail to moderate out sites that go to significant lengths to track users. In addition, we perform several case studies which highlight deceptive behavior and modern techniques used by some domains to avoid detection, monetize traffic, or otherwise exploit their viewers. #R##N#Overall, we find that despite recent improvements in mechanisms for detecting malicious browser extensions, ad-blocking, and browser warnings, users of free illegal live streaming services are still exposed to deceptive ads, malicious browser extensions, scams, and extensive tracking. We conclude with insights into the ecosystem and recommendations for addressing the challenges highlighted by this study.

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)