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: "non asymptotic and asymptotic analyses of information processing on markov chains"
  Abstract: In this paper, we derive non-asymptotic achievability and converse bounds on the source coding with/without side-information, the random number generation with/without side-information, and the channel coding for the regular channel. Our bounds are efficiently computable in the sense that the computational complexity does not depend on the block length. We also characterize the asymptotic behaviors of the large deviation regime and the moderate deviation regime by using our bounds, which implies that our bounds are asymptotically tight in those regimes. We also show the second order rates of those problems, and derive single letter forms of the variances characterizing the second order rates.

Connected through hyperedge HE-1 (induced by source paper "semi finite length analysis for information theoretic tasks"):
  with members:
    - "physical layer security for rf satellite channels in the finite length regime"
    - "uniform random number generation from markov chains non asymptotic and asymptotic analyses"
    - "strong converse for a degraded wiretap channel via active hypothesis testing"
    - "a tight upper bound for the third order asymptotics for most discrete memoryless channels"
    - "the log volume of optimal codes for memoryless channels asymptotically within a few nats"
    - "exponential decreasing rate of leaked information in universal random privacy amplification"
    - "information spectrum approach to second order coding rate in channel coding"
    - "second order asymptotics in fixed length source coding and intrinsic randomness"

Connected through hyperedge HE-2 (induced by source paper "secrecy and robustness for active attack in secure network coding and its application to network quantum key distribution"):
  with members:
    - "secure network code for adaptive and active attacks with no randomness in intermediate nodes"
    - "universal construction of cheater identifiable secret sharing against rushing cheaters without honest majority"
    - "universal secure multiplex network coding with dependent and non uniform messages"
    - "secure multi source multicast"
    - "quantum inspired secure wireless communication protocol under spatial and local gaussian noise assumptions"
    - "secure wireless communication under spatial and local gaussian noise assumptions"
    - "relative generalized rank weight of linear codes and its applications to network coding"
    - "coding against a limited view adversary the effect of causality and feedback"

Connected through hyperedge HE-3 (induced by source paper "second order analysis for joint source channel coding with markovian source"):
  with members:
    - "uniform random number generation from markov chains non asymptotic and asymptotic analyses"
    - "finite length analyses for source and channel coding on markov chains"
    - "lossy joint source channel coding in the finite blocklength regime"
    - "the dispersion of joint source channel coding"
    - "information spectrum approach to second order coding rate in channel coding"
    - "second order asymptotics in fixed length source coding and intrinsic randomness"

Connected through hyperedge HE-4 (induced by source paper "finite length bounds for joint source channel coding with markovian source and additive channel noise to achieve large and moderate deviation bounds"):
  with members:
    - "lossy joint source channel coding in the finite blocklength regime"
    - "the dispersion of joint source channel coding"

Connected through hyperedge HE-5 (induced by source paper "security analysis of varepsilon almost dual universal 2 hash functions smoothing of min entropy versus smoothing of renyi entropy of order 2"):
  with members:
    - "secure multiplex coding with dependent and non uniform multiple messages"
    - "uniform random number generation from markov chains non asymptotic and asymptotic analyses"
    - "equivocations exponents and second order coding rates under various r enyi information measures"
    - "tight exponential analysis of universally composable privacy amplification and its applications"
    - "secret key generation from gaussian sources using lattice hashing"
    - "non asymptotic analysis of privacy amplification via renyi entropy and inf spectral entropy"
    - "exponential decreasing rate of leaked information in universal random privacy amplification"
    - "strongly secure communications over the two way wiretap channel"

Connected through hyperedge HE-6 (induced by source paper "uniform random number generation from markov chains non asymptotic and asymptotic analyses"):
  with members:
    - "security analysis of varepsilon almost dual universal 2 hash functions smoothing of min entropy versus smoothing of renyi entropy of order 2"
    - "second order coding rates for channels with state"
    - "second order resolvability intrinsic randomness and fixed length source coding for mixed sources information spectrum approach"
    - "tight exponential analysis of universally composable privacy amplification and its applications"
    - "non asymptotic analysis of privacy amplification via renyi entropy and inf spectral entropy"
    - "exponential decreasing rate of leaked information in universal random privacy amplification"
    - "universal strongly secure network coding with dependent and non uniform messages"
    - "moderate deviations of lossy source coding for discrete and gaussian sources"

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.IT(Information Theory)