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: "hypothesis testing under maximal leakage privacy constraints"
  Abstract: The problem of publishing privacy-guaranteed data for hypothesis testing is studied using the maximal leakage (ML) as a metric for privacy and the type-II error exponent as the utility metric. The optimal mechanism (random mapping) that maximizes utility for a bounded leakage guarantee is determined for the entire leakage range for binary datasets. For non-binary datasets, approximations in the high privacy and high utility regimes are developed. The results show that, for any desired leakage level, maximizing utility forces the ML privacy mechanism to reveal partial to complete knowledge about a subset of the source alphabet. The results developed on maximizing a convex function over a polytope may also of an independent interest.

Connected through hyperedge HE-1 (induced by source paper "a practical approach to navigating the tradeoff between privacy and precise utility"):
  with members:
    - "the utility cost of robust privacy guarantees"
    - "an estimation theoretic view of privacy"
    - "on maximal correlation mutual information and data privacy"
    - "maximal correlation secrecy"
    - "from the information bottleneck to the privacy funnel"
    - "utility privacy tradeoffs in databases an information theoretic approach"
    - "privacy against statistical inference"
    - "smart meter privacy a utility privacy framework"

Connected through hyperedge HE-2 (induced by source paper "privacy aware distributed hypothesis testing"):
  with members:
    - "privacy aware smart metering progress and challenges"
    - "distributed hypothesis testing with privacy constraints"
    - "technical privacy metrics a systematic survey"
    - "distributed hypothesis testing based on unequal error protection codes"
    - "privacy against a hypothesis testing adversary"
    - "on the reliability function of distributed hypothesis testing under optimal detection"
    - "distributed hypothesis testing over discrete memoryless channels"
    - "hypothesis testing under mutual information privacy constraints in the high privacy regime"

Connected through hyperedge HE-3 (induced by source paper "estimation efficiency under privacy constraints"):
  with members:
    - "technical privacy metrics a systematic survey"
    - "generalizing bottleneck problems"
    - "privacy aware guessing efficiency"
    - "hypothesis testing under mutual information privacy constraints in the high privacy regime"
    - "principal inertia components and applications"
    - "privacy aware mmse estimation"
    - "notes on information theoretic privacy"
    - "information extraction under privacy constraints"

Connected through hyperedge HE-4 (induced by source paper "distributed hypothesis testing cooperation and concurrent detection"):
  with members:
    - "optimal rate exponent region for a class of hypothesis testing against conditional independence problems"
    - "vector gaussian ceo problem under logarithmic loss and applications"
    - "distributed hypothesis testing with collaborative detection"
    - "distributed hypothesis testing with privacy constraints"
    - "distributed hypothesis testing with concurrent detections"
    - "on hypothesis testing against independence with multiple decision centers"
    - "hypothesis testing under mutual information privacy constraints in the high privacy regime"
    - "distributed hypothesis testing over noisy channels"

Connected through hyperedge HE-5 (induced by source paper "profile based privacy for locally private computations"):
  with members:
    - "the structure of optimal private tests for simple hypotheses"
    - "on the theory and practice of privacy preserving bayesian data analysis"
    - "rappor randomized aggregatable privacy preserving ordinal response"
    - "on the relation between identifiability differential privacy and mutual information privacy"
    - "geo indistinguishability differential privacy for location based systems"
    - "calibrating data to sensitivity in private data analysis"
    - "distributed learning communication complexity and privacy"
    - "differentially private empirical risk minimization"

Connected through hyperedge HE-6 (induced by source paper "distributed detection with empirically observed statistics"):
  with members:
    - "second order asymptotically optimal statistical classification"
    - "anonymous heterogeneous distributed detection optimal decision rules error exponents and the price of anonymity"
    - "distributed hypothesis testing with privacy constraints"
    - "asymptotically optimal matching of multiple sequences to source distributions and training sequences"
    - "asymmetric evaluations of erasure and undetected error probabilities"
    - "privacy against statistical inference"
    - "data fusion trees for detection does architecture matter"

Connected through hyperedge HE-7 (induced by source paper "optimal rate exponent region for a class of hypothesis testing against conditional independence problems"):
  with members:
    - "distributed hypothesis testing with concurrent detections"
    - "on hypothesis testing against independence with multiple decision centers"
    - "an outer bound for the vector gaussian ceo problem"
    - "multiterminal source coding under logarithmic loss"
    - "rate region of the quadratic gaussian two encoder source coding problem"

Connected through hyperedge HE-8 (induced by source paper "on the robustness of information theoretic privacy measures and mechanisms"):
  with members:
    - "data disclosure under perfect sample privacy"
    - "privacy against brute force inference attacks"
    - "estimation efficiency under privacy constraints"
    - "data privacy for a rho recoverable function"
    - "an operational approach to information leakage"
    - "the utility cost of robust privacy guarantees"
    - "privacy under hard distortion constraints"
    - "a tunable measure for information leakage"

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)