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: "security smells in infrastructure as code scripts"
  Abstract: Context: Security smells are coding patterns in source code that are indicative of security weaknesses. As infrastructure as code (IaC) scripts are used to provision cloud-based servers and systems at scale, security smells in IaC scripts could be used to enable malicious users to exploit vulnerabilities in the provisioned systems. Goal: The goal of this paper is to help practitioners avoid insecure coding practices while developing infrastructure as code (IaC) scripts through an empirical study of security smells in IaC scripts. Methodology: We apply qualitative analysis with 3,339 IaC scripts to identify security smells for IaC scripts written in three languages: Ansible, Chef, and Puppet. We construct a static analysis tool called Security Linter for Infrastructure as Code scripts (SLIC) to automatically identify security smells in 61,097 scripts collected from 1,093 open source software repositories. We also submit bug reports for 1,500 randomly-selected smell occurrences identified from the 61,097 scripts. Results: We identify nine security smells for IaC scripts. By applying SLIC on 61,097 IaC scripts we identify 64,356 occurrences of security smells that included 9,092 hard-coded passwords. We observe agreement for 130 of the responded 187 bug reports, which suggests the relevance of security smells for IaC scripts amongst practitioners. Conclusion: We observe security smells to be prevalent in IaC scripts. We recommend practitioners to rigorously inspect the presence of the identified security smells in IaC scripts using (i) code review, and (ii) static analysis tools.

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)