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 "oblivious storage with low i o overhead"):
  Abstract: We study oblivious storage (OS), a natural way to model privacy-preserving data outsourcing where a client, Alice, stores sensitive data at an honest-but-curious server, Bob. We show that Alice can hide both the content of her data and the pattern in which she accesses her data, with high probability, using a method that achieves O(1) amortized rounds of communication between her and Bob for each data access. We assume that Alice and Bob exchange small messages, of size $O(N^{1/c})$, for some constant $c\ge2$, in a single round, where $N$ is the size of the data set that Alice is storing with Bob. We also assume that Alice has a private memory of size $2N^{1/c}$. These assumptions model real-world cloud storage scenarios, where trade-offs occur between latency, bandwidth, and the size of the client's private memory.

Includes members:
  Member "oblivious ram simulation with efficient worst case access overhead":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "stronger lower bounds for online oram")
  Member "privacy preserving group data access via stateless oblivious ram simulation":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "dr sgx automated and adjustable side channel protection for sgx using data location randomization")
  Member "privacy preserving access of outsourced data via oblivious ram simulation":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "lower bounds for oblivious near neighbor search")
  Member "de amortized cuckoo hashing provable worst case performance and experimental results":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "fully dynamic space efficient dictionaries and filters with constant number of memory accesses")

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)