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: "on the randomness of independent experiments"
  Abstract: Given a probability distribution P, what is the minimum amount of bits needed to store a value x sampled according to P, such that x can later be recovered (except with some small probability)? Or, what is the maximum amount of uniform randomness that can be extracted from x? Answering these and similar information-theoretic questions typically boils down to computing so-called smooth entropies. In this paper, we derive explicit and almost tight bounds on the smooth entropies of n-fold product distributions.

Connected through hyperedge HE-1 (induced by source paper "explicit codes for the wiretap channel a unified design framework"):
  with members:
    - "a new wiretap channel model and its strong secrecy capacity"
    - "empirical and strong coordination via soft covering with polar codes"
    - "coding schemes for achieving strong secrecy at negligible cost"
    - "semantic security capacity for wiretap channels of type ii"
    - "achieving secrecy capacity of the wiretap channel and broadcast channel with a confidential component"
    - "polar coding for the broadcast channel with confidential messages a random binning analogy"
    - "how to achieve the capacity of asymmetric channels"
    - "an information theoretic approach to secret sharing"

Connected through hyperedge HE-2 (induced by source paper "a capacity achieving one message key agreement with finite blocklength analysis"):
  with members:
    - "secret key agreement general capacity and second order asymptotics"
    - "polar coding for secret key generation"
    - "fuzzy extractors how to generate strong keys from biometrics and other noisy data"
    - "oblivious transfer amplification"

Connected through hyperedge HE-3 (induced by source paper "a one round key agreement protocol with information theoretic security"):
  with members:
    - "secret key agreement general capacity and second order asymptotics"
    - "fuzzy extractors how to generate strong keys from biometrics and other noisy data"

Connected through hyperedge HE-4 (induced by source paper "universal hashing for information theoretic security"):
  with members:
    - "secure multiplex coding with dependent and non uniform multiple messages"
    - "equivocations exponents and second order coding rates under various r enyi information measures"
    - "converses for secret key agreement and secure computing"
    - "secret key agreement general capacity and second order asymptotics"
    - "achieving secrecy capacity of the wiretap channel and broadcast channel with a confidential component"
    - "a new upperbound for the oblivious transfer capacity of discrete memoryless channels"
    - "strong converse for a degraded wiretap channel via active hypothesis testing"
    - "semantically secure lattice codes for the gaussian wiretap channel"

Connected through hyperedge HE-5 (induced by source paper "semantically secure coding scheme achieving the capacity of a gaussian wiretap channel"):
  with members:
    - "secure multiplex coding with dependent and non uniform multiple messages"
    - "equivocations exponents and second order coding rates under various r enyi information measures"
    - "converses for secret key agreement and secure computing"
    - "secret key agreement general capacity and second order asymptotics"
    - "a new upperbound for the oblivious transfer capacity of discrete memoryless channels"
    - "the complexity of estimating r enyi entropy"
    - "strong converse for a degraded wiretap channel via active hypothesis testing"
    - "semantically secure lattice codes for the gaussian wiretap channel"

Connected through hyperedge HE-6 (induced by source paper "upper tail estimates with combinatorial proofs"):
  with members:
    - "constructing a pseudorandom generator requires an almost linear number of calls"

Connected through hyperedge HE-7 (induced by source paper "tight exponential analysis of universally composable privacy amplification and its applications"):
  with members:
    - "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 privacy amplification cannot be obtained by encoder of slepian wolf code"
    - "information spectrum approach to second order coding rate in channel coding"
    - "second order asymptotics in fixed length source coding and intrinsic randomness"
    - "commitment capacity of discrete memoryless channels"

Connected through hyperedge HE-8 (induced by source paper "polynomial time semantically secure encryption achieving the secrecy capacity"):
  with members:
    - "a cryptographic treatment of the wiretap channel"
    - "how to construct polar codes"
    - "achieving the secrecy capacity of wiretap channels using polar codes"
    - "nested polar codes for wiretap and relay channels"
    - "strong secrecy for erasure wiretap channels"
    - "secrecy achieving polar coding for binary input memoryless symmetric wire tap channels"
    - "invertible extractors and wiretap protocols"
    - "fuzzy extractors how to generate strong keys from biometrics and other noisy data"

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)