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: "privacy preserving distributed learning with secret gradient descent"
  Abstract: In many important application domains of machine learning, data is a privacy-sensitive resource. In addition, due to the growing complexity of the models, single actors typically do not have sufficient data to train a model on their own. Motivated by these challenges, we propose Secret Gradient Descent (SecGD), a method for training machine learning models on data that is spread over different clients while preserving the privacy of the training data. We achieve this by letting each client add temporary noise to the information they send to the server during the training process. They also share this noise in separate messages with the server, which can then subtract it from the previously received values. By routing all data through an anonymization network such as Tor, we prevent the server from knowing which messages originate from the same client, which in turn allows us to show that breaking a client's privacy is computationally intractable as it would require solving a hard instance of the subset sum problem. This setup allows SecGD to work in the presence of only two honest clients and a malicious server, and without the need for peer-to-peer connections.

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)