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: "uncovering social network sybils in the wild"
  Abstract: Sybil accounts are fake identities created to unfairly increase the power or resources of a single malicious user. Researchers have long known about the existence of Sybil accounts in online communities such as file-sharing systems, but have not been able to perform large scale measurements to detect them or measure their activities. In this paper, we describe our efforts to detect, characterize and understand Sybil account activity in the Renren online social network (OSN). We use ground truth provided by Renren Inc. to build measurement based Sybil account detectors, and deploy them on Renren to detect over 100,000 Sybil accounts. We study these Sybil accounts, as well as an additional 560,000 Sybil accounts caught by Renren, and analyze their link creation behavior. Most interestingly, we find that contrary to prior conjecture, Sybil accounts in OSNs do not form tight-knit communities. Instead, they integrate into the social graph just like normal users. Using link creation timestamps, we verify that the large majority of links between Sybil accounts are created accidentally, unbeknownst to the attacker. Overall, only a very small portion of Sybil accounts are connected to other Sybils with social links. Our study shows that existing Sybil defenses are unlikely to succeed in today's OSNs, and we must design new techniques to effectively detect and defend against Sybil attacks.

Connected through hyperedge HE-1 (induced by source paper "fawkes protecting personal privacy against unauthorized deep learning models"):
  with members:
    - "strong baseline defenses against clean label poisoning attacks"
    - "anonymousnet natural face de identification with measurable privacy"
    - "hiding faces in plain sight disrupting ai face synthesis with adversarial perturbations"
    - "fooling automated surveillance cameras adversarial patches to attack person detection"
    - "making an invisibility cloak real world adversarial attacks on object detectors"
    - "advhat real world adversarial attack on arcface face id system"
    - "using honeypots to catch adversarial attacks on neural networks"
    - "detecting backdoor attacks on deep neural networks by activation clustering"

Connected through hyperedge HE-2 (induced by source paper "twitter bot detection using bidirectional long short term memory neural networks and word embeddings"):
  with members:
    - "on the use of bert for neural machine translation"
    - "dual fofe net neural models for entity linking with pagerank"
    - "online human bot interactions detection estimation and characterization"
    - "botornot a system to evaluate social bots"
    - "dna inspired online behavioral modeling and its application to spambot detection"
    - "the rise of social bots"
    - "speech recognition with deep recurrent neural networks"
    - "distributed representations of words and phrases and their compositionality"

Connected through hyperedge HE-3 (induced by source paper "the art of social bots a review and a refined taxonomy"):
  with members:
    - "cashtag piggybacking uncovering spam and bot activity in stock microblogs on twitter"
    - "sybilfuse combining local attributes with global structure to perform robust sybil detection"
    - "lobo evaluation of generalization deficiencies in twitter bot classifiers"
    - "false information on web and social media a survey"
    - "measuring social spam and the effect of bots on information diffusion in social media"
    - "detecting influence campaigns in social networks using the ising model"
    - "botnet campaign detection on twitter"
    - "an unsupervised approach to detect spam campaigns that use botnets on twitter"

Connected through hyperedge HE-4 (induced by source paper "better safe than sorry an adversarial approach to improve social bot detection"):
  with members:
    - "social fingerprinting detection of spambot groups through dna inspired behavioral modeling"
    - "spectrum based deep neural networks for fraud detection"
    - "hardening classifiers against evasion the good the bad and the ugly"
    - "holoscope topology and spike aware fraud detection"
    - "the paradigm shift of social spambots evidence theories and tools for the arms race"
    - "online human bot interactions detection estimation and characterization"
    - "botivist calling volunteers to action using online bots"
    - "dna inspired online behavioral modeling and its application to spambot detection"

Connected through hyperedge HE-5 (induced by source paper "rtbust exploiting temporal patterns for botnet detection on twitter"):
  with members:
    - "influence of fake news in twitter during the 2016 us presidential election"
    - "social fingerprinting detection of spambot groups through dna inspired behavioral modeling"
    - "relational autoencoder for feature extraction"
    - "holoscope topology and spike aware fraud detection"
    - "the paradigm shift of social spambots evidence theories and tools for the arms race"
    - "botivist calling volunteers to action using online bots"
    - "botornot a system to evaluate social bots"
    - "dna inspired online behavioral modeling and its application to spambot detection"

Connected through hyperedge HE-6 (induced by source paper "resource competitive sybil defenses"):
  with members:
    - "proof of work without all the work"
    - "secure one way interactive communication"
    - "torbricks blocking resistant tor bridge distribution"
    - "interactive communication with unknown noise rate"
    - "bitcoin ng a scalable blockchain protocol"
    - "the mason test a defense against sybil attacks in wireless networks without trusted authorities"
    - "self healing computation"
    - "the sybil attacks and defenses a survey"

Connected through hyperedge HE-7 (induced by source paper "the history of digital spam"):
  with members:
    - "online human bot interactions detection estimation and characterization"
    - "the darpa twitter bot challenge"
    - "the rise of social bots"
    - "manipulation and abuse on social media by emilio ferrara with ching man au yeung as coordinator"
    - "on facebook most ties are weak"
    - "an experimental comparison of naive bayesian and keyword based anti spam filtering with personal e mail messages"

Connected through hyperedge HE-8 (induced by source paper "scalable similarity joins of tokenized strings"):
  with members:
    - "paying for likes understanding facebook like fraud using honeypots"
    - "v smart join a scalable mapreduce framework for all pair similarity joins of multisets and vectors"
    - "pass join a partition based method for similarity joins"
    - "benchmarking declarative approximate selection predicates"

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.SI(Social and Information Networks)