human: Given a hyperedge-centered hypergraph: <hypergraph>, where the center hyperedge is induced by one source paper and its member nodes are the cited papers.

Details of the hypergraph:
Center hyperedge (induced by source paper "gaussian secure source coding and wyner s common information"):
  Abstract: We study secure source-coding with causal disclosure, under the Gaussian distribution. The optimality of Gaussian auxiliary random variables is shown in various scenarios. We explicitly characterize the tradeoff between the rates of communication and secret key. This tradeoff is the result of a mutual information optimization under Markov constraints. As a corollary, we deduce a general formula for Wyner's Common Information in the Gaussian setting.

Includes members:
  Member "an extremal inequality for long markov chains":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "extracting robust and accurate features via a robust information bottleneck")
  Member "secure coordination with a two sided helper":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "strong secrecy for cooperative broadcast channels")
  Member "the lossy common information of correlated sources":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "characterization of conditional independence and weak realizations of multivariate gaussian random variables applications to networks")
  Member "wyner s common information generalizations and a new lossy source coding interpretation":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "on exact and infty r enyi common informations")
  Member "a bit of secrecy for gaussian source compression":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "a rate distortion based secrecy system with side information at the decoders")
  Member "optimal equivocation in secrecy systems a special case of distortion based characterization":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "secure coordination with a two sided helper")
  Member "on secure source coding with side information at the encoder":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "secure lossy source coding for some classes of helper and gray wyner models")
  Member "distributed channel synthesis":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "gaussian approximation of quantization error for estimation from compressed data")

Question: Please tell me which class the source paper 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)