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: "semantically secure coding scheme achieving the capacity of a gaussian wiretap channel"
  Abstract: We extend a recently proposed wiretap coding scheme to the Gaussian wiretap channel and show that it is semantically-secure. Denoting by SNR the signal-to-noise ratio of the eavesdropper's channel, the proposed scheme converts a transmission code of rate R for the channel of the legitimate receiver into a code of rate R - 0.5 log(1 + SNR) for the Gaussian wiretap channel. The conversion has a polynomial complexity in the codeword length and the proposed scheme achieves semantic security. In particular, when the underlying transmission code is capacity achieving, this scheme achieves the secrecy capacity of the Gaussian wiretap channel. Our security analysis relies on a single-shot bound on the mutual information between the message and the eavesdropper's observation for the proposed scheme, which may be of independent interest.

Connected through hyperedge HE-1 (induced by source paper "semantic security capacity for wiretap channels of type ii"):
  with members:
    - "secure multiplex coding with dependent and non uniform multiple messages"
    - "the likelihood encoder for lossy compression"
    - "soft covering with high probability"
    - "the henchman problem measuring secrecy by the minimum distortion in a list"
    - "a rate distortion based secrecy system with side information at the decoders"
    - "semantically secure lattice codes for the gaussian wiretap channel"
    - "the likelihood encoder for lossy source compression"
    - "informational divergence approximations to product distributions"

Connected through hyperedge HE-2 (induced by source paper "the mimo wiretap channel decomposed"):
  with members:
    - "optimal signaling for secure communications over gaussian mimo wiretap channels"
    - "an algorithm for global maximization of secrecy rates in gaussian mimo wiretap channels"
    - "joint unitary triangularization for gaussian multi user mimo networks"
    - "joint unitary triangularization for mimo networks"
    - "achieving the secrecy capacity of wiretap channels using polar codes"
    - "strong secrecy from channel resolvability"
    - "construction of wiretap codes from ordinary channel codes"
    - "the secrecy capacity of the mimo wiretap channel"

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)