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 "differential private stream processing of energy consumption"):
  Abstract: A number of applications benefit from continuously releasing streams of personal data statistics. The process, however, poses significant privacy risks. Motivated by an application in energy systems, this paper presents OptStream, a novel algorithm for releasing differential private data streams. OptStream is a 4-step procedure consisting of sampling, perturbation, reconstruction, and post-processing modules. The sampling module selects a small set of points to access privately in each period of interest, the perturbation module adds noise to the sampled data points to guarantee privacy, the reconstruction module re-assembles the non-sampling data points from the perturbed sampled points, and the post-processing module uses convex optimization over the private output of the previous modules, as well as the private answers of additional queries on the data stream, to ensure consistency of the data's salient features. OptStream is used to release a real data stream from the largest transmission operator in Europe. Experimental results show that OptStream not only improves the accuracy of the state-of-the-art by at least one order of magnitude on this application domain, but it is also able to ensure accurate load forecasting based on the private data.

Includes members:
  Member "collecting telemetry data privately":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "locally private hypothesis selection")
  Member "building a rappor with the unknown privacy preserving learning of associations and data dictionaries":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "wireless federated learning with local differential privacy")
  Member "optimality of the laplace mechanism in differential privacy":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "the podium mechanism improving on the laplace and staircase mechanisms")
  Member "private decayed predicate sums on streams":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "money cannot buy everything trading infinite location data streams with bounded individual privacy loss")
  Member "geo indistinguishability differential privacy for location based systems":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "local information privacy and its application to privacy preserving data aggregation")
  Member "calibrating data to sensitivity in private data analysis":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "locally private hypothesis selection")

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)