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: "towards detecting compromised accounts on social networks"
  Abstract: Compromising social network accounts has become a profitable course of action for cybercriminals. By hijacking control of a popular media or business account, attackers can distribute their malicious messages or disseminate fake information to a large user base. The impacts of these incidents range from a tarnished reputation to multi-billion dollar monetary losses on financial markets. In our previous work, we demonstrated how we can detect large-scale compromises (i.e., so-called campaigns) of regular online social network users. In this work, we show how we can use similar techniques to identify compromises of individual high-profile accounts. High-profile accounts frequently have one characteristic that makes this detection reliable -- they show consistent behavior over time. We show that our system, were it deployed, would have been able to detect and prevent three real-world attacks against popular companies and news agencies. Furthermore, our system, in contrast to popular media, would not have fallen for a staged compromise instigated by a US restaurant chain for publicity reasons.

Connected through hyperedge HE-1 (induced by source paper "towards understanding the information ecosystem through the lens of multiple web communities"):
  with members:
    - "characterizing the use of images by state sponsored troll accounts on twitter"
    - "characterizing the use of images in state sponsored information warfare operations by russian trolls on twitter"
    - "what is gab a bastion of free speech or an alt right echo chamber"
    - "a quantitative approach to understanding online antisemitism"
    - "who let the trolls out towards understanding state sponsored trolls"
    - "disinformation warfare understanding state sponsored trolls on twitter and their influence on the web"
    - "mobilizing the trump train understanding collective action in a political trolling community"
    - "false information on web and social media a survey"

Connected through hyperedge HE-2 (induced by source paper "the mass fake news and cognition security"):
  with members:
    - "the role of user profile for fake news detection"
    - "influence of fake news in twitter during the 2016 us presidential election"
    - "studying fake news via network analysis detection and mitigation"
    - "techniques for interpretable machine learning"
    - "declare debunking fake news and false claims using evidence aware deep learning"
    - "fake news a survey of research detection methods and opportunities"
    - "opinion dynamics with varying susceptibility to persuasion"
    - "deepinf social influence prediction with deep learning"

Connected through hyperedge HE-3 (induced by source paper "on preempting advanced persistent threats using probabilistic graphical models"):
  with members:
    - "vulnerable open source dependencies counting those that matter"
    - "on the inability of markov models to capture criticality in human mobility"
    - "snorkel rapid training data creation with weak supervision"
    - "catching worms trojan horses and pups unsupervised detection of silent delivery campaigns"
    - "thou shalt not depend on me analysing the use of outdated javascript libraries on the web"
    - "attack analysis results for adversarial engagement 1 of the darpa transparent computing program"
    - "opengm a c library for discrete graphical models"

Connected through hyperedge HE-4 (induced by source paper "understanding troll writing as a linguistic phenomenon"):
  with members:
    - "disinformation warfare understanding state sponsored trolls on twitter and their influence on the web"
    - "an exploration of word embedding initialization in deep learning tasks"
    - "adam a method for stochastic optimization"
    - "efficient estimation of word representations in vector space"

Connected through hyperedge HE-5 (induced by source paper "a survey on the security of pervasive online social networks posns"):
  with members:
    - "a framework for mitigating zero day attacks in iot"
    - "nhad neuro fuzzy based horizontal anomaly detection in online social networks"
    - "self enforcing game theory based resource allocation for lorawan assisted public safety communications"
    - "managing service heterogeneity using osmotic computing"
    - "netspam a network based spam detection framework for reviews in online social media"
    - "a privacy preserving community based p2p osns using broadcast encryption supporting recommendation mechanism"
    - "extension of mih to support fpmipv6 for optimized heterogeneous handover"
    - "analyzing resilience of interest based social networks against node and link failures"

Connected through hyperedge HE-6 (induced by source paper "disinformation warfare understanding state sponsored trolls on twitter and their influence on the web"):
  with members:
    - "hunting for troll comments in news community forums"
    - "tracking the digital traces of russian trolls distinguishing the roles and strategy of trolls on twitter"
    - "still out there modeling and identifying russian troll accounts on twitter"
    - "characterizing the use of images by state sponsored troll accounts on twitter"
    - "who let the trolls out towards understanding state sponsored trolls"
    - "an army of me sockpuppets in online discussion communities"
    - "what s in a name understanding profile name reuse on twitter"
    - "has the online discussion been manipulated quantifying online discussion authenticity within online social media"

Connected through hyperedge HE-7 (induced by source paper "collective classification of spam campaigners on twitter a hierarchical meta path based approach"):
  with members:
    - "poised spotting twitter spam off the beaten paths"
    - "dial one for scam a large scale analysis of technical support scams"
    - "botornot a system to evaluate social bots"
    - "detecting smart spammers on social network a topic model approach"
    - "the rise of social bots"
    - "detecting criminal organizations in mobile phone networks"
    - "meta path based collective classification in heterogeneous information networks"
    - "hetesim a general framework for relevance measure in heterogeneous networks"

Connected through hyperedge HE-8 (induced by source paper "catching loosely synchronized behavior in face of camouflage"):
  with members:
    - "fairjudge trustworthy user prediction in rating platforms"
    - "birdnest bayesian inference for ratings fraud detection"
    - "edgecentric anomaly detection in edge attributed networks"
    - "spotting suspicious link behavior with fbox an adversarial perspective"
    - "sybilbelief a semi supervised learning approach for structure based sybil detection"
    - "community detection via semi synchronous label propagation algorithms"
    - "finding deceptive opinion spam by any stretch of the imagination"

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)