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: "an unattended study of users performing security critical tasks under adversarial noise"
  Abstract: Author(s): Kaczmarek, Tyler; Kobsa, Alfred; Sy, Robert; Tsudik, Gene | Abstract: User errors while performing security-critical tasks can lead to undesirable or even disastrous consequences. One major factor influencing mistakes and failures is complexity of such tasks, which has been studied extensively in prior research. Another important issue which hardly received any attention is the impact of both accidental and intended distractions on users performing security-critical tasks. In particular, it is unclear whether, and to what extent, unexpected sensory cues (e.g., auditory or visual) can influence user behavior and/or trigger mistakes. Better understanding of the effects of intended distractions will help clarify their role in adversarial models. As part of the research effort described in this paper, we administered a range of naturally occurring -- yet unexpected -- sounds while study participants attempted to perform a security-critical task. We found that, although these auditory cues lowered participants' failure rates, they had no discernible effect on their task completion times. To this end, we overview some relevant literature that explains these somewhat counter-intuitive findings. Conducting a thorough and meaningful study on user errors requires a large number of participants, since errors are typically infrequent and should not be instigated more than once per subject. To reduce the effort of running numerous subjects, we developed a novel experimental setup that was fully automated and unattended. We discuss our experience with this setup and highlight the pros and cons of generalizing its usage.

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.HC(Human-Computer Interaction)