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 hmm based behavior modeling approach for continuous mobile authentication"
  Abstract: This paper studies continuous authentication for touch interface based mobile devices. A Hidden Markov Model (HMM) based behavioral template training approach is presented, which does not require training data from other subjects other than the owner of the mobile. The stroke patterns of a user are modeled using a continuous left-right HMM. The approach models the horizontal and vertical scrolling patterns of a user since these are the basic and mostly used interactions on a mobile device. The effectiveness of the proposed method is evaluated through extensive experiments using the Touchalytics database which comprises of touch data over time. The results show that the performance of the proposed approach is better than the state-of-the-art method. Index Terms— Touch pattern, Continuous authentication, Hidden Markov Model, Behavioral biometric, Security

Connected through hyperedge HE-1 (induced by source paper "actions speak louder than pass words passive authentication of smartphone users via deep temporal features"):
  with members:
    - "multilock mobile active authentication based on multiple biometric and behavioral patterns"
    - "active authentication on mobile devices via stylometry application usage web browsing and gps location"
    - "active user authentication for smartphones a challenge data set and benchmark results"
    - "learning human identity from motion patterns"
    - "hmog new behavioral biometric features for continuous authentication of smartphone users"
    - "adam a method for stochastic optimization"
    - "touchalytics on the applicability of touchscreen input as a behavioral biometric for continuous authentication"

Connected through hyperedge HE-2 (induced by source paper "kid on the phone toward automatic detection of children on mobile devices"):
  with members:
    - "tap based user authentication for smartwatches"
    - "implicit smartphone user authentication with sensors and contextual machine learning"
    - "illusionpin shoulder surfing resistant authentication using hybrid images"
    - "an hmm based multi sensor approach for continuous mobile authentication"
    - "user generated free form gestures for authentication security and memorability"
    - "touchalytics on the applicability of touchscreen input as a behavioral biometric for continuous authentication"
    - "silentsense silent user identification via dynamics of touch and movement behavioral biometrics"

Connected through hyperedge HE-3 (induced by source paper "an hmm based multi sensor approach for continuous mobile authentication"):
  with members:
    - "touchalytics on the applicability of touchscreen input as a behavioral biometric for continuous authentication"
    - "silentsense silent user identification via dynamics of touch and movement behavioral biometrics"

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)