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 "ensei efficient secure inference via frequency domain homomorphic convolution for privacy preserving visual recognition"):
  Abstract: In this work, we propose ENSEI, a secure inference (SI) framework based on the frequency-domain secure convolution (FDSC) protocol for the efficient execution of privacy-preserving visual recognition. Our observation is that, under the combination of homomorphic encryption and secret sharing, homomorphic convolution can be obliviously carried out in the frequency domain, significantly simplifying the related computations. We provide protocol designs and parameter derivations for number-theoretic transform (NTT) based FDSC. In the experiment, we thoroughly study the accuracy-efficiency trade-offs between time- and frequency-domain homomorphic convolution. With ENSEI, compared to the best known works, we achieve 5--11x online time reduction, up to 33x setup time reduction, and up to 10x reduction in the overall inference time. A further 33% of bandwidth reductions can be obtained on binary neural networks with only 1% of accuracy degradation on the CIFAR-10 dataset.

Includes members:
  Member "privacy preserving image based localization":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "revealing scenes by inverting structure from motion reconstructions")
  Member "xonn xnor based oblivious deep neural network inference":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "nass optimizing secure inference via neural architecture search")
  Member "towards privacy preserving visual recognition via adversarial training a pilot study":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "an adversarial learning framework for preserving users anonymity in face based emotion recognition")
  Member "low latency privacy preserving inference":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "she a fast and accurate privacy preserving deep neural network via leveled tfhe and logarithmic data representation")
  Member "gazelle a low latency framework for secure neural network inference":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "deep quaternion features for privacy protection")
  Member "stealing hyperparameters in machine learning":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "dynamic backdoor attacks against machine learning models")
  Member "faster cryptonets leveraging sparsity for real world encrypted inference":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "heaan demystified accelerating fully homomorphic encryption through architecture centric analysis and optimization")
  Member "deepsecure scalable provably secure deep learning":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "optimizing privacy preserving outsourced convolutional neural network predictions")

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)