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 "private heavy hitters and range queries in the shuffled model"):
  Abstract: An exciting new development in differential privacy is the shuffled model, which makes it possible to circumvent the large error lower bounds that are typically incurred in the local model, while relying on much weaker trust assumptions than in the central model. In this work, we study two basic statistical problems, namely, heavy hitters and $d$-dimensional range counting queries, in the shuffled model of privacy. For both problems we devise algorithms with polylogarithmic communication per user and polylogarithmic error; a consequence is an algorithm for approximating the median with similar communication and error. These bounds significantly improve on what is possible in the local model of differential privacy, where the error must provably grow polynomially with the number of users.

Includes members:
  Member "communication complexity in locally private distribution estimation and heavy hitters":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "on the power of multiple anonymous messages")
  Member "scalable and differentially private distributed aggregation in the shuffled model":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "pure differentially private summation from anonymous messages")
  Member "tight lower bounds for locally differentially private selection":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "locally private hypothesis selection")
  Member "answering range queries under local differential privacy":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "consistent and accurate frequency oracles under local differential privacy")
  Member "practical locally private heavy hitters":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "a workload adaptive mechanism for linear queries under local differential privacy")
  Member "marginal release under local differential privacy":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "outis crypto assisted differential privacy on untrusted servers")
  Member "heavy hitters and the structure of local privacy":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "pure differentially private summation from anonymous messages")
  Member "prochlo strong privacy for analytics in the crowd":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "pure differentially private summation from anonymous messages")

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)