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: "matching anonymized and obfuscated time series to users profiles"
  Abstract: Many popular applications use traces of user data to offer various services to their users. However, even if user data is anonymized and obfuscated, a user's privacy can be compromised through the use of statistical matching techniques that match a user trace to prior user behavior. In this work, we derive the theoretical bounds on the privacy of users in such a scenario. We build on our recent study in the area of location privacy, in which we introduced formal notions of location privacy for anonymization-based location privacy-protection mechanisms. Here we derive the fundamental limits of user privacy when both anonymization and obfuscation-based protection mechanisms are applied to users' time series of data. We investigate the impact of such mechanisms on the trade-off between privacy protection and user utility. We first study achievability results for the case where the time-series of users are governed by an i.i.d. process. The converse results are proved both for the i.i.d. case as well as the more general Markov chain model. We demonstrate that as the number of users in the network grows, the obfuscation-anonymization plane can be divided into two regions: in the first region, all users have perfect privacy; and, in the second region, no user has privacy.

Connected through hyperedge HE-1 (induced by source paper "privacy aware time series data sharing with deep reinforcement learning"):
  with members:
    - "the long road to computational location privacy a survey"
    - "privacy cost trade off in a smart meter system with a renewable energy source and a rechargeable battery"
    - "privacy aware location sharing with deep reinforcement learning"
    - "privacy aware smart metering progress and challenges"
    - "achieving perfect location privacy in wireless devices using anonymization"
    - "smart meter privacy with renewable energy and a finite capacity battery"
    - "information theoretic privacy for smart metering systems with a rechargeable battery"
    - "adam a method for stochastic optimization"

Connected through hyperedge HE-2 (induced by source paper "asymptotic limits of privacy in bayesian time series matching"):
  with members:
    - "asymptotic loss in privacy due to dependency in gaussian traces"
    - "privacy of dependent users against statistical matching"
    - "fundamental limits of invisible flow fingerprinting"
    - "privacy against statistical matching inter user correlation"
    - "towards provably invisible network flow fingerprints"
    - "where you are is who you are user identification by matching statistics"
    - "achieving perfect location privacy in wireless devices using anonymization"
    - "asymptotically optimal matching of multiple sequences to source distributions and training sequences"

Connected through hyperedge HE-3 (induced by source paper "improving privacy in graphs through node addition"):
  with members:
    - "seeded graph matching efficient algorithms and theoretical guarantees"
    - "achieving perfect location privacy in wireless devices using anonymization"
    - "optimal de anonymization in random graphs with community structure"
    - "an efficient reconciliation algorithm for social networks"
    - "de anonymizing social networks"
    - "neighbor specific bgp more flexible routing policies while improving global stability"

Connected through hyperedge HE-4 (induced by source paper "a concentration of measure approach to database de anonymization"):
  with members:
    - "fundamental limits of database alignment"
    - "typicality matching for pairs of correlated graphs"
    - "an information theoretic framework for active de anonymization in social networks based on group memberships"
    - "seeded graph matching efficient algorithms and theoretical guarantees"
    - "where you are is who you are user identification by matching statistics"

Connected through hyperedge HE-5 (induced by source paper "leveraging prior knowledge asymmetries in the design of location privacy preserving mechanisms"):
  with members:
    - "privacy of dependent users against statistical matching"
    - "is geo indistinguishability what you are looking for"
    - "a survey of point of interest recommendation in location based social networks"
    - "optimal geo indistinguishable mechanisms for location privacy"

Connected through hyperedge HE-6 (induced by source paper "privacy of dependent users against statistical matching"):
  with members:
    - "asymptotic limits of privacy in bayesian time series matching"
    - "a concentration of measure approach to database de anonymization"
    - "single server single message online private information retrieval with side information"
    - "asymptotic loss in privacy due to dependency in gaussian traces"
    - "fundamental limits of database alignment"
    - "community detection with side information exact recovery under the stochastic block model"
    - "matching graphs with community structure a concentration of measure approach"
    - "on the performance of a canonical labeling for matching correlated erdős renyi graphs"

Connected through hyperedge HE-7 (induced by source paper "privacy with estimation guarantees"):
  with members:
    - "the utility cost of robust privacy guarantees"
    - "generalizing bottleneck problems"
    - "privacy preserving adversarial networks"
    - "renyi differential privacy"
    - "principal inertia components and applications"
    - "hypothesis testing under maximal leakage privacy constraints"
    - "an estimation theoretic view of privacy"
    - "privacy aware mmse estimation"

Connected through hyperedge HE-8 (induced by source paper "fundamental limits of covert bit insertion in packets"):
  with members:
    - "first and second order asymptotics in covert communication"
    - "asymptotic loss in privacy due to dependency in gaussian traces"
    - "embedding covert information in broadcast communications"
    - "fundamental limits of invisible flow fingerprinting"
    - "privacy preserving mhealth data release with pattern consistency"
    - "privacy against statistical matching inter user correlation"
    - "towards provably invisible network flow fingerprints"
    - "covert wireless communication with artificial noise generation"

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.IT(Information Theory)