human: Given a node-centered hypergraph: <hypergraph>, where nodes represent papers and hyperedges represent sets of papers co-cited by a source paper.

Details of the hypergraph:
Center node: "differentially private oblivious ram"
  Abstract: In this work, we investigate if statistical privacy can enhance the performance of ORAM mechanisms while providing rigorous privacy guarantees. We propose a formal and rigorous framework for developing ORAM protocols with statistical security viz., a differentially private ORAM (DP-ORAM). We present Root ORAM, a family of DP-ORAMs that provide a tunable, multi-dimensional trade-off between the desired bandwidth overhead, local storage and system security. #R##N#We theoretically analyze Root ORAM to quantify both its security and performance. We experimentally demonstrate the benefits of Root ORAM and find that (1) Root ORAM can reduce local storage overhead by more than 2X for a privacy budget of \epsilon = 4, significantly enhancing performance in memory limited platforms such as trusted execution environments, and (2) Root ORAM allows tunable trade-offs between bandwidth, storage, and privacy, reducing bandwidth overheads by upto 2X-10X (at the cost of increased storage/statistical privacy), enabling significant reductions in ORAM access latencies for cloud environments. We also analyze the privacy guarantees of DP-ORAMs through the lens of information theoretic metrics of Shannon entropy and Min-entropy [12]. Finally, Root ORAM is ideally suited for applications which have a similar access pattern, and we showcase its utility via the application of Private Information Retrieval.

Connected through hyperedge HE-1 (induced by source paper "what storage access privacy is achievable with small overhead"):
  with members:
    - "accessing data while preserving privacy"
    - "root oram a tunable differentially private oblivious ram"
    - "the melbourne shuffle improving oblivious storage in the cloud"
    - "calibrating data to sensitivity in private data analysis"
    - "privacy preserving access of outsourced data via oblivious ram simulation"

Connected through hyperedge HE-2 (induced by source paper "an algorithmic framework for differentially private data analysis on trusted processors"):
  with members:
    - "the privacy blanket of the shuffle model"
    - "amplification by shuffling from local to central differential privacy via anonymity"
    - "distributed differential privacy via shuffling"
    - "practical locally private heavy hitters"
    - "cachezoom how sgx amplifies the power of cache attacks"
    - "software grand exposure sgx cache attacks are practical"
    - "towards practical differential privacy for sql queries"
    - "prochlo strong privacy for analytics in the crowd"

Connected through hyperedge HE-3 (induced by source paper "mix oram using delegate shuffles"):
  with members:
    - "zig zag sort a simple deterministic data oblivious sorting algorithm running in o n log n time"
    - "anonymous card shuffling and its applications to parallel mixnets"
    - "privacy preserving group data access via stateless oblivious ram simulation"
    - "towards practical oblivious ram"
    - "randomized shellsort a simple oblivious sorting algorithm"

Question: Please tell me which class the center node 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)