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: "providing confidential cloud based fall detection from remote sensor data using multi party computation"
  Abstract: Fall detection systems are concerned with rapidly detecting the occurrence of falls from elderly and disabled users using data from a body-worn inertial measurement unit (IMU), which is typically used in conjunction with machine learning-based classification. Such systems, however, necessitate the collection of high-resolution measurements that can violate users' privacy, such as revealing their gait, activities of daily living (ADLs), and relative position using dead reckoning. In this paper, for the first time, we present the design, implementation and evaluation of applying multi-party computation (MPC) to IMU-based fall detection for assuring the confidentiality of device measurements. The system is evaluated in a cloud-based setting that precludes parties from learning the underlying data using three parties deployed in geographically disparate locations in three cloud configurations. Using a publicly-available dataset comprising fall data from real-world users, we explore the applicability of derivative-based features to mitigate the complexity of MPC-based operations in a state-of-the-art fall detection system. We demonstrate that MPC-based fall detection from IMU measurements is both feasible and practical, executing in 365.2 milliseconds, which falls well below the required time window for on-device data acquisition (750ms).

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)