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 "guidelines for implementing and auditing differentially private systems"):
  Abstract: Differential privacy is an information theoretic constraint on algorithms and code. It provides quantification of privacy leakage and formal privacy guarantees that are currently considered the gold standard in privacy protections. In this paper we provide an initial set of ``best practices'' for developing differentially private platforms, techniques for unit testing that are specific to differential privacy, guidelines for checking if differential privacy is being applied correctly in an application, and recommendations for parameter settings. The genesis of this paper was an initiative by Facebook and Social Science One to provide social science researchers with programmatic access to a URL-shares dataset. In order to maximize the utility of the data for research while protecting privacy, researchers should access the data through an interactive platform that supports differential privacy. #R##N#The intention of this paper is to provide guidelines and recommendations that can generally be re-used in a wide variety of systems. For this reason, no specific platforms will be named, except for systems whose details and theory appear in academic papers.

Includes members:
  Member "differentially private objective perturbation beyond smoothness and convexity":
    also connected through other hyperedges:
      (none)
  Member "identifying cache based side channels through secret augmented abstract interpretation":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "a compiler assisted scheduler for detecting and mitigating cache based side channel attacks")
  Member "fuzzi a three level logic for differential privacy":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "duet an expressive higher order language and linear type system for statically enforcing differential privacy")
  Member "an economic analysis of privacy protection and statistical accuracy as social choices":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "crypt epsilon crypto assisted differential privacy on untrusted servers")
  Member "private selection from private candidates":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "differentially private mixed type data generation for unsupervised learning")
  Member "ektelo a framework for defining differentially private computations":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "a workload adaptive mechanism for linear queries under local differential privacy")
  Member "detecting violations of differential privacy":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "evaluating differentially private machine learning in practice")
  Member "how to use heuristics for differential privacy":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "an equivalence between private classification and online prediction")

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)