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: "what s the gist privacy preserving aggregation of user profiles"
  Abstract: Over the past few years, online service providers have started gathering increasing amounts of personal information to build user profiles and monetize them with advertisers and data brokers. Users have little control of what information is processed and are often left with an all-or-nothing decision between receiving free services or refusing to be profiled. This paper explores an alternative approach where users only disclose an aggregate model -- the "gist" -- of their data. We aim to preserve data utility and simultaneously provide user privacy. We show that this approach can be efficiently supported by letting users contribute encrypted and differentially-private data to an aggregator. The aggregator combines encrypted contributions and can only extract an aggregate model of the underlying data. We evaluate our framework on a dataset of 100,000 U.S. users obtained from the U.S. Census Bureau and show that (i) it provides accurate aggregates with as little as 100 users, (ii) it generates revenue for both users and data brokers, and (iii) its overhead is appreciably low.

Connected through hyperedge HE-1 (induced by source paper "towards extending noiseless privacy dependent data and more practical approach"):
  with members:
    - "practical fault tolerant data aggregation"
    - "calibrating data to sensitivity in private data analysis"
    - "on sampling anonymization and differential privacy or k anonymization meets differential privacy"

Connected through hyperedge HE-2 (induced by source paper "a game theoretic study on non monetary incentives in data analytics projects with privacy implications"):
  with members:
    - "budget feasible mechanisms for experimental design"
    - "linear regression as a non cooperative game"
    - "crowd assisted search for price discrimination in e commerce first results"
    - "conducting truthful surveys cheaply"
    - "take it or leave it running a survey when privacy comes at a cost"
    - "truthful mechanisms for agents that value privacy"
    - "selling privacy at auction"
    - "approximately optimal mechanism design via differential privacy"

Connected through hyperedge HE-3 (induced by source paper "controlled data sharing for collaborative predictive blacklisting"):
  with members:
    - "espresso efficient privacy preserving evaluation of sample set similarity"
    - "predictive blacklisting as an implicit recommendation system"
    - "evaluating the utility of anonymized network traces for intrusion detection"
    - "sharing computer network logs for security and privacy a motivation for new methodologies of anonymization"

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)