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 "helen maliciously secure coopetitive learning for linear models"):
  Abstract: Many organizations wish to collaboratively train machine learning models on their combined datasets for a common benefit (e.g., better medical research, or fraud detection). However, they often cannot share their plaintext datasets due to privacy concerns and/or business competition. In this paper, we design and build Helen, a system that allows multiple parties to train a linear model without revealing their data, a setting we call coopetitive learning. Compared to prior secure training systems, Helen protects against a much stronger adversary who is malicious and can compromise m-1 out of m parties. Our evaluation shows that Helen can achieve up to five orders of magnitude of performance improvement when compared to training using an existing state-of-the-art secure multi-party computation framework.

Includes members:
  Member "drynx decentralized secure verifiable system for statistical queries and machine learning on distributed datasets":
    also connected through other hyperedges:
      (none)
  Member "fine pruning defending against backdooring attacks on deep neural networks":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "entangled watermarks as a defense against model extraction")
  Member "spectre attacks exploiting speculative execution":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "towards probabilistic verification of machine unlearning")
  Member "the secret sharer measuring unintended neural network memorization extracting secrets":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "membership inference attacks on sequence to sequence models is my data in your machine translation system")
  Member "manipulating machine learning poisoning attacks and countermeasures for regression learning":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "secure and robust machine learning for healthcare a survey")
  Member "chameleon a hybrid secure computation framework for machine learning applications":
    also connected through other hyperedges:
      - Hyperedge HE-5 (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-6 (induced by source paper "deep quaternion features for privacy protection")
  Member "prio private robust and scalable computation of aggregate statistics":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "encode shuffle analyze privacy revisited formalizations and empirical evaluation")

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)