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 "manipulation attacks in local differential privacy"):
  Abstract: Local differential privacy is a widely studied restriction on distributed algorithms that collect aggregates about sensitive user data, and is now deployed in several large systems. We initiate a systematic study of a fundamental limitation of locally differentially private protocols: they are highly vulnerable to adversarial manipulation. While any algorithm can be manipulated by adversaries who lie about their inputs, we show that any non-interactive locally differentially private protocol can be manipulated to a much greater extent. Namely, when the privacy level is high or the input domain is large, an attacker who controls a small fraction of the users in the protocol can completely obscure the distribution of the users' inputs. We also show that existing protocols differ greatly in their resistance to manipulation, even when they offer the same accuracy guarantee with honest execution. Our results suggest caution when deploying local differential privacy and reinforce the importance of efficient cryptographic techniques for emulating mechanisms from central differential privacy in distributed settings.

Includes members:
  Member "distributed differential privacy via shuffling":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "pure differentially private summation from anonymous messages")
  Member "practical locally private heavy hitters":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "a workload adaptive mechanism for linear queries under local differential privacy")
  Member "optimal schemes for discrete distribution estimation under locally differential privacy":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "a workload adaptive mechanism for linear queries under local differential privacy")
  Member "heavy hitters and the structure of local privacy":
    also connected through other hyperedges:
      - Hyperedge HE-4 (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-5 (induced by source paper "pure differentially private summation from anonymous messages")
  Member "the complexity of computing the optimal composition of differential privacy":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "gaussian differential privacy")
  Member "local private efficient protocols for succinct histograms":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "pure differentially private summation from anonymous messages")
  Member "rappor randomized aggregatable privacy preserving ordinal response":
    also connected through other hyperedges:
      - Hyperedge HE-8 (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.DS(Data Structures and Algorithms)