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 "arm2gc succinct garbled processor for secure computation"):
  Abstract: We present ARM2GC, a novel secure computation framework based on Yao's Garbled Circuit (GC) protocol and the ARM processor. It allows users to develop privacy-preserving applications using standard high-level programming languages (e.g., C) and compile them using off-the-shelf ARM compilers (e.g., gcc-arm). The main enabler of this framework is the introduction of SkipGate, an algorithm that dynamically omits the communication and encryption cost of the gates whose outputs are independent of the private data. SkipGate greatly enhances the performance of ARM2GC by omitting costs of the gates associated with the instructions of the compiled binary, which is known by both parties involved in the computation. Our evaluation on benchmark functions demonstrates that ARM2GC not only outperforms the current GC frameworks that support high-level languages, it also achieves efficiency comparable to the best prior solutions based on hardware description languages. Moreover, in contrast to previous high-level frameworks with domain-specific languages and customized compilers, ARM2GC relies on standard ARM compiler which is rigorously verified and supports programs written in the standard syntax.

Includes members:
  Member "xonn xnor based oblivious deep neural network inference":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "nass optimizing secure inference via neural architecture search")
  Member "chameleon a hybrid secure computation framework for machine learning applications":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "cryptanalytic extraction of neural network models")
  Member "gazelle a low latency framework for secure neural network inference":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "deep quaternion features for privacy protection")

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)