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 multiplex coding over interference channel with confidential messages"):
  Abstract: In this paper, an inner bound on the capacity region of two-user interference channels with two confidential messages has been proposed. With secure multiplex coding, we show that the Han-Kobayashi region can be achieved with strong security requirement. The equivocation rate for a collection of secret messages has also been evaluated, when the length of the message is finite or the information rate is high, our result provides a good approximation for bounding the worst case equivocation rate. Index Terms—Information theoretic security, capacity region, interference channel, secure multiplex coding, strong security.

Includes members:
  Member "exponential decreasing rate of leaked information in universal random privacy amplification":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "communication for generating correlation a unifying survey")
  Member "secure multiplex coding with a common message":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "universal secure multiplex network coding with dependent and non uniform messages")
  Member "secure multiplex network coding":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "secure network code for adaptive and active attacks with no randomness in intermediate nodes")
  Member "strong security and separated code constructions for the broadcast channels with confidential messages":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "plausible deniability over broadcast channels")
  Member "interference channels with strong secrecy":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "perfect secrecy in physical layer network coding systems from structured interference")
  Member "discrete memoryless interference and broadcast channels with confidential messages secrecy rate regions":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "cognitive radio networks an information theoretic perspective")
  Member "secure multiplex coding to attain the channel capacity in wiretap channels":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "secure multiplex coding with dependent and non uniform multiple messages")

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)