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: "physical integrity attack detection of surveillance camera with deep learning based video frame interpolation"
  Abstract: Surveillance cameras, which is a form of Cyber Physical System, are deployed extensively to provide visual surveillance monitoring of activities of interest or anomalies. However, these cameras are at risks of physical security attacks against their physical attributes or configuration like tampering of their recording coverage, camera positions or recording configurations like focus and zoom factors. Such adversarial alteration of physical configuration could also be invoked through cyber security attacks against the camera's software vulnerabilities to administratively change the camera's physical configuration settings. When such Cyber Physical attacks occur, they affect the integrity of the targeted cameras that would in turn render these cameras ineffective in fulfilling the intended security functions. There is a significant measure of research work in detection mechanisms of cyber-attacks against these Cyber Physical devices, however it is understudied area with such mechanisms against integrity attacks on physical configuration. This research proposes the use of the novel use of deep learning algorithms to detect such physical attacks originating from cyber or physical spaces. Additionally, we proposed the novel use of deep learning-based video frame interpolation for such detection that has comparatively better performance to other anomaly detectors in spatiotemporal environments.

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)