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: "brokenstrokes on the in security of wireless keyboards"
  Abstract: Wireless devices resorting to event-triggered communications have been proved to suffer critical privacy issues, due to the intrinsic leakage associated with radio frequency emissions. In this paper, we move the attack frontier forward by proposing BrokenStrokes: an inexpensive, easy to implement, efficient, and effective attack able to detect the typing of a predefined keyword by only eavesdropping the communication channel used by the wireless keyboard. BrokenStrokes achieves its goal when the eavesdropping antenna is up to 15 meters from the target keyboard. We prove the attack succeeds regardless of the encryption scheme, the communication protocol, the presence of radio noise, and the presence of physical obstacles. We tested BrokenStrokes in three real scenarios (close to the keyboard--e.g., the eavesdropping device is concealed under the desk--, wall separation-- eavesdropping from next office--, and eavesdropping from the public street--into the house of one of the co-authors), under the following conditions: presence of radio noise, testing arbitrary long keystroke sequences, and varying several system parameters. Performance are striking: BrokenStrokes detects the presence of a keyword among the user's keystrokes in 90% of cases when the eavesdropping antenna is placed in the proximity of the keyboard (up to 20 cm), while it guarantees at least 73% success rate when the eavesdropping antenna is up to 15 meters far away from the target. We discuss the rationale for the attack, its logical flow, and we detail the experimental setting and the algorithmic machinery adopted. Finally, we discuss potential countermeasures and sketch some future research directions. The data utilized in this paper have been released as open-source to allow practitioners, industries, and academia to verify our claims and use them as a basis for further developments.

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)