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: "path person authentication using trace histories"
  Abstract: In this paper, a solution to the problem of Active Authentication using trace histories is addressed. Specifically, the task is to perform user verification on mobile devices using historical location traces of the user as a function of time. Considering the movement of a human as a Markovian motion, a modified Hidden Markov Model (HMM)-based solution is proposed. The proposed method, namely the Marginally Smoothed HMM (MSHMM), utilizes the marginal probabilities of location and timing information of the observations to smooth-out the emission probabilities while training. Hence, it can efficiently handle unforeseen observations during the test phase. The verification performance of this method is compared to a sequence matching (SM) method, a Markov Chain-based method (MC) and an HMM with basic Laplace Smoothing (HMM-lap). Experimental results using the location information of the UMD Active Authentication Dataset-02 (UMDAA02) and the GeoLife dataset are presented. The proposed MSHMM method outperforms the compared methods in terms of equal error rate (EER). Additionally, the effects of different parameters on the proposed method are discussed.

Connected through hyperedge HE-1 (induced by source paper "be captcha detecting human behavior in smartphone interaction using multiple inbuilt sensors"):
  with members:
    - "multilock mobile active authentication based on multiple biometric and behavioral patterns"
    - "actions speak louder than pass words passive authentication of smartphone users via deep temporal features"
    - "hacking google recaptcha v3 using reinforcement learning"
    - "mobiface a novel dataset for mobile face tracking in the wild"
    - "continuous authentication of smartphones based on application usage"
    - "active user authentication for smartphones a challenge data set and benchmark results"
    - "the partially observable hidden markov model and its application to keystroke dynamics"
    - "touchalytics on the applicability of touchscreen input as a behavioral biometric for continuous authentication"

Connected through hyperedge HE-2 (induced by source paper "multilock mobile active authentication based on multiple biometric and behavioral patterns"):
  with members:
    - "continuous authentication of smartphones based on application usage"
    - "active user authentication for smartphones a challenge data set and benchmark results"
    - "the partially observable hidden markov model and its application to keystroke dynamics"

Connected through hyperedge HE-3 (induced by source paper "continuous authentication of smartphones based on application usage"):
  with members:
    - "effect of context in swipe gesture based continuous authentication on smartphones"
    - "predicting smartphone battery life based on comprehensive and real time usage data"
    - "active authentication on mobile devices via stylometry application usage web browsing and gps location"
    - "secure pick up implicit authentication when you start using the smartphone"
    - "a survey on behavioral biometric authentication on smartphones"
    - "active user authentication for smartphones a challenge data set and benchmark results"
    - "learning human identity from motion patterns"
    - "touchalytics on the applicability of touchscreen input as a behavioral biometric for continuous authentication"

Connected through hyperedge HE-4 (induced by source paper "you are how you walk uncooperative mocap gait identification for video surveillance with incomplete and noisy data"):
  with members:
    - "gait recognition from motion capture data"
    - "an evaluation framework and database for mocap based gait recognition methods"
    - "active user authentication for smartphones a challenge data set and benchmark results"
    - "learning robust features for gait recognition by maximum margin criterion"
    - "person re identification by unsupervised video matching"
    - "walker independent features for gait recognition from motion capture data"
    - "person re identification past present and future"

Connected through hyperedge HE-5 (induced by source paper "continuous user authentication via unlabeled phone movement patterns"):
  with members:
    - "active user authentication for smartphones a challenge data set and benchmark results"
    - "authenticating users through their arm movement patterns"
    - "hmog new behavioral biometric features for continuous authentication of smartphone users"

Connected through hyperedge HE-6 (induced by source paper "promises and challenges in continuous tracking utilizing amino acids in skin secretions for active multi factor biometric authentication for cybersecurity"):
  with members:
    - "active user authentication for smartphones a challenge data set and benchmark results"

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.CV(Computer Vision and Pattern Recognition)