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 "adding a helper can totally remove the secrecy constraints in interference channel"):
  Abstract: In many communication channels, secrecy constraints usually incur a penalty in capacity, as well as generalized degrees-of-freedom (GDoF). In this work we show an interesting observation that, adding a helper can totally remove the penalty in sum GDoF, for a two-user symmetric Gaussian interference channel. For the interference channel where each transmitter sends a message to an intended receiver without secrecy constraints, the sum GDoF is a well-known "W" curve, characterized by Etkin-Tse-Wang in 2008. If the secrecy constraints are imposed on this interference channel, where the message of each transmitter must be secure from the unintended receiver (eavesdropper), then a GDoF penalty is incurred and the secure sum GDoF is reduced to a modified "W" curve, derived by Chen recently. In this work we show that, by adding a helper into this interference channel with secrecy constraints, the secure sum GDoF turns out to be a "W" curve, which is the same as the sum GDoF of the setting without secrecy constraints. The proposed scheme is based on the cooperative jamming and a careful signal design such that the jamming signal of the helper is aligned at a specific direction and power level with the information signals of the transmitters, which allows to totally remove the penalty in GDoF due to the secrecy constraints. Furthermore, the estimation approaches of noise removal and signal separation due to the rational independence are used in the secure rate analysis.

Includes members:
  Member "secure communication over interference channel to jam or not to jam":
    also connected through other hyperedges:
      - Hyperedge HE-1 (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 with no eavesdropper csit":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "adding common randomness can remove the secrecy constraints in communication networks")
  Member "towards a constant gap sum capacity result for the gaussian wiretap channel with a helper":
    also connected through other hyperedges:
      - Hyperedge HE-3 (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-4 (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-5 (induced by source paper "multi antenna coded content delivery with caching a low complexity solution")
  Member "principles of physical layer security in multiuser wireless networks a survey":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "angle aware user cooperation for secure massive mimo in rician fading channel")
  Member "interference alignment for secrecy":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "adding common randomness can remove the secrecy constraints in communication networks")
  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)