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 "security in the gaussian interference channel weak and moderately weak interference regimes"):
  Abstract: We consider a secure communication scenario through the two-user Gaussian interference channel: each transmitter (user) has a confidential message to send reliably to its intended receiver while keeping it secret from the other receiver. Prior work investigated the performance of two different approaches for this scenario; i.i.d. Gaussian random codes and real alignment of structured codes. While the latter achieves the optimal sum secure degrees of freedom (s.d.o.f.), its extension to finite SNR regimes is challenging. In this paper, we propose a new achievability scheme for the weak and the moderately weak interference regimes, in which the reliability as well as the confidentiality of the transmitted messages are maintained at any finite SNR value. Our scheme uses lattice structure, structured jamming codewords, and lattice alignment in the encoding and the asymmetric compute-and-forward strategy in the decoding. We show that our lower bound on the sum secure rates scales linearly with log(SNR) and hence, it outperforms i.i.d. Gaussian random codes. Furthermore, we show that our achievable result is asymptotically optimal. Finally, we provide a discussion on an extension of our scheme to K>2 users.

Includes members:
  Member "compute and forward can buy secrecy cheap":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "preserving confidentiality in the gaussian broadcast channel using compute and forward")
  Member "finite snr regime analysis of the gaussian wiretap multiple access channel":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "adding common randomness can remove the secrecy constraints in communication networks")
  Member "secure degrees of freedom of one hop wireless networks":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "towards an algebraic network information theory simultaneous joint typicality decoding")
  Member "real interference alignment exploiting the potential of single antenna systems":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "multi antenna coded content delivery with caching a low complexity solution")
  Member "secure degrees of freedom of k user gaussian interference channels a unified view":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "adding common randomness can remove the secrecy constraints in communication networks")
  Member "the approximate sum capacity of the symmetric gaussian k user interference channel":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "private information retrieval over gaussian mac")
  Member "compute and forward harnessing interference through structured codes":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "private information retrieval over gaussian mac")
  Member "discrete memoryless interference and broadcast channels with confidential messages secrecy rate regions":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "cognitive radio networks an information theoretic perspective")

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)