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 "differentially private sql with bounded user contribution"):
  Abstract: Differential privacy (DP) provides formal guarantees that the output of a database query does not reveal too much information about any individual present in the database. While many differentially private algorithms have been proposed in the scientific literature, there are only a few end-to-end implementations of differentially private query engines. Crucially, existing systems assume that each individual is associated with at most one database record, which is unrealistic in practice. We propose a generic and scalable method to perform differentially private aggregations on databases, even when individuals can each be associated with arbitrarily many rows. We express this method as an operator in relational algebra, and implement it in an SQL engine. To validate this system, we test the utility of typical queries on industry benchmarks, and verify its correctness with a stochastic test framework we developed. We highlight the promises and pitfalls learned when deploying such a system in practice, and we publish its core components as open-source software.

Includes members:
  Member "sok differential privacies":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "local distribution obfuscation via probability coupling")
  Member "detecting violations of differential privacy":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "guidelines for implementing and auditing differentially private systems")
  Member "shrinkwrap differentially private query processing in private data federations":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "crypt epsilon crypto assisted differential privacy on untrusted servers")
  Member "plausible deniability for privacy preserving data synthesis":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "privgen preserving privacy of sequences through data generation")
  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 "towards practical differential privacy for sql queries":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "linkedin s audience engagements api a privacy preserving data analytics system at scale")
  Member "concentrated differential privacy simplifications extensions and lower bounds":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "reasoning about generalization via conditional mutual information")
  Member "differential privacy an estimation theory based method for choosing epsilon":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "mitigating query flooding parameter duplication attack on regression models with high dimensional gaussian mechanism")

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)