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: "ghostimage perception domain attacks against vision based object classification systems"
  Abstract: In vision-based object classification systems, imaging sensors perceive the environment and then objects are detected and classified for decision-making purposes. Vulnerabilities in the perception domain enable an attacker to inject false data into the sensor which could lead to unsafe consequences. In this work, we focus on camera-based systems and propose GhostImage attacks, with the goal of either creating a fake perceived object or obfuscating the object's image that leads to wrong classification results. This is achieved by remotely projecting adversarial patterns into camera-perceived images, exploiting two common effects in optical imaging systems, namely lens flare/ghost effects, and auto-exposure control. To improve the robustness of the attack to channel perturbations, we generate optimal input patterns by integrating adversarial machine learning techniques with a trained end-to-end channel model. We realize GhostImage attacks with a projector, and conducted comprehensive experiments, using three different image datasets, in indoor and outdoor environments, and three different cameras. We demonstrate that GhostImage attacks are applicable to both autonomous driving and security surveillance scenarios. Experiment results show that, depending on the projector-camera distance, attack success rates can reach as high as 100%.

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)