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 "the secrecy capacity region of the degraded vector gaussian broadcast channel"):
  Abstract: In this paper, we consider a scenario where a source node wishes to broadcast two confidential messages for two respective receivers via a Gaussian MIMO broadcast channel. A wire-tapper also receives the transmitted signal via another MIMO channel. It is assumed that the channels are degraded and the wire-tapper has the worst channel. We establish the capacity region of this scenario. Our achievability scheme is a combination of the superposition of Gaussian codes and randomization within the layers which we will refer to as Secret Superposition Coding. For the outerbound, we use the notion of enhanced channel to show that the secret superposition of Gaussian codes is optimal. It is shown that we only need to enhance the channels of the legitimate receivers, and the channel of the eavesdropper remains unchanged.

Includes members:
  Member "secure transmission with multiple antennas ii the mimome wiretap channel":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "multi antenna jamming in covert communication")
  Member "the secrecy capacity region of the gaussian mimo multi receiver wiretap channel":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "secure relaying in non orthogonal multiple access trusted and untrusted scenarios")
  Member "multiple input multiple output gaussian broadcast channels with confidential messages":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "mimo multiple access channel with an arbitrarily varying eavesdropper")
  Member "the secrecy capacity region of the gaussian mimo broadcast channel":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "secured communication over frequency selective fading channels a practical vandermonde precoding")
  Member "a note on the secrecy capacity of the multi antenna wiretap channel":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "on the secrecy rate region of a fading multiple antenna gaussian broadcast channel with confidential messages and partial csit")
  Member "an extremal inequality motivated by multiterminal information theoretic problems":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "vector gaussian successive refinement with degraded side information")

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)