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 "secure joint source channel coding with side information"):
  Abstract: In this work, the problem of transmitting an i.i.d Gaussian source over an i.i.d Gaussian wiretap channel with an i.i.d Gaussian side information is considered. The intended receiver is assumed to have a certain minimum SNR and the eavesdropper is assumed to have a strictly lower SNR compared to the intended receiver. The objective is minimizing the distortion of source reconstruction at the intended receiver. In this work, it is shown that unlike the Gaussian wiretap channel without side information, Shannon's source-channel separation coding scheme is not optimum in the sense of achieving the minimum distortion. Three hybrid digital-analog secure joint source channel coding schemes are then proposed which achieve the minimum distortion. The first coding scheme is based on Costa's dirty paper coding scheme and wiretap channel coding scheme when the analog source is not explicitly quantized. The second coding scheme is based on the superposition of the secure digital signal and the hybrid digital-analog signal. It is shown that for the problem of communicating a Gaussian source over a Gaussian wiretap channel with side information, there exists an infinite family of optimum secure joint source-channel coding scheme. In the third coding scheme, the quantized signal and the analog error signal are explicitly superimposed. It is shown that this scheme provides an infinite family of optimum secure joint source-channel channel coding schemes with a variable number of binning. Finally, the proposed secure hybrid digital-analog schemes are analyzed under the main channel SNR mismatch. It is proven that the proposed schemes can give a graceful degradation of distortion with SNR under SNR mismatch, i.e., when the actual SNR is larger than the designed SNR.

Includes members:
  Member "the secrecy capacity region of the degraded vector gaussian broadcast channel":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "secure hybrid digital analog coding with side information at the receiver")
  Member "transmitting an analog gaussian source over a gaussian wiretap channel under snr mismatch":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "joint source channel secrecy using uncoded schemes towards secure source broadcast")
  Member "superimposed coded and uncoded transmissions of a gaussian source over the gaussian channel":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "secure hybrid digital analog coding with side information at the receiver")
  Member "on the secrecy capacity of fading channels":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "parallel bcc with one common and two confidential messages and imperfect csit")

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)