human: Given a hyperedge-centered hypergraph: <hypergraph>, where the center hyperedge is induced by one source paper and its member nodes are the cited papers.

Details of the hypergraph:
Center hyperedge (induced by source paper "local distribution obfuscation via probability coupling"):
  Abstract: We introduce a general model for the local obfuscation of probability distributions by probabilistic perturbation, e.g., by adding differentially private noise, and investigate its theoretical properties. Specifically, we relax a notion of distribution privacy (DistP) by generalizing it to divergence, and propose local obfuscation mechanisms that provide divergence distribution privacy. To provide f-divergence distribution privacy, we prove that probabilistic perturbation noise should be added proportionally to the Earth mover’s distance between the probability distributions that we want to make indistinguishable. Furthermore, we introduce a local obfuscation mechanism, which we call a coupling mechanism, that provides divergence distribution privacy while optimizing the utility of obfuscated data by using exact/approximate auxiliary information on the input distributions we want to protect.

Includes members:
  Member "local obfuscation mechanisms for hiding probability distributions":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "privacy preserving multiple tensor factorization for synthesizing large scale location traces")
  Member "sok differential privacies":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "differentially private sql with bounded user contribution")
  Member "profile based privacy for locally private computations":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "local obfuscation mechanisms for hiding probability distributions")
  Member "utility optimized local differential privacy mechanisms for distribution estimation":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "mitigating query flooding parameter duplication attack on regression models with high dimensional gaussian mechanism")
  Member "renyi differential privacy":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "guidelines for implementing and auditing differentially private systems")
  Member "on the compositionality of quantitative information flow":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "local obfuscation mechanisms for hiding probability distributions")
  Member "differential privacy as a mutual information constraint":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "local information privacy and its application to privacy preserving data aggregation")
  Member "concentrated differential privacy":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "privately learning markov random fields")

Question: Please tell me which class the source paper 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)