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: "detecting malicious logins as graph anomalies"
  Abstract: Authenticated lateral movement via compromised accounts is a common adversarial maneuver that is challenging to discover with signature- or rules-based intrusion detection systems. In this work a behavior-based approach to detecting malicious logins to novel systems indicative of lateral movement is presented, in which a user's historical login activity is used to build a model of putative "normal" behavior. This historical login activity is represented as a collection of daily login graphs, which encode authentications among accessed systems. Each system, or graph vertex, is described by a set of graph centrality measures that characterize it and the local topology of its login graph. The unsupervised technique of non-negative matrix factorization is then applied to this set of features to assign each vertex to a role that summarizes how the system participates in logins. The reconstruction error quantifying how well each vertex fits into its role is then computed, and the statistics of this error can be used to identify outlier vertices that correspond to systems involved in unusual logins. We test this technique with a small cohort of privileged accounts using real login data from an operational enterprise network. The ability of the method to identify malicious logins among normal activity is tested with simulated graphs of login activity representative of adversarial lateral movement. We find that the method is generally successful at detecting a broad range of lateral movement for each user, with false positive rates significantly lower than those resulting from alerts based solely on login novelty.

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)