human: Given a node-centered hypergraph: <hypergraph>, where nodes represent papers and hyperedges represent sets of papers co-cited by a source paper.

Details of the hypergraph:
Center node: "3 receiver broadcast channels with common and confidential messages"
  Abstract: This paper establishes inner bounds on the secrecy capacity regions for the general 3-receiver broadcast channel with one common and one confidential message sets. We consider two setups. The first is when the confidential message is to be sent to two receivers and kept secret from the third receiver. Achievability is established using indirect decoding, Wyner wiretap channel coding, and the new idea of generating secrecy from a publicly available superposition codebook. The inner bound is shown to be tight for a class of reversely degraded broadcast channels and when both legitimate receivers are less noisy than the third receiver. The second setup investigated in this paper is when the confidential message is to be sent to one receiver and kept secret from the other two receivers. Achievability in this case follows from Wyner wiretap channel coding and indirect decoding. This inner bound is also shown to be tight for several special cases.

Connected through hyperedge HE-1 (induced by source paper "can marton coding alone ensure individual secrecy"):
  with members:
    - "a simplified coding scheme for the broadcast channel with complementary receiver side information under individual secrecy constraints"
    - "the secure two receiver broadcast channel with one sided receiver side information"
    - "individual secrecy for broadcast channels with receiver side information"
    - "individual secrecy for the broadcast channel"

Connected through hyperedge HE-2 (induced by source paper "the secure two receiver broadcast channel with one sided receiver side information"):
  with members:
    - "a simplified coding scheme for the broadcast channel with complementary receiver side information under individual secrecy constraints"
    - "individual secrecy for broadcast channels with receiver side information"
    - "individual secrecy for the broadcast channel"
    - "discrete memoryless interference and broadcast channels with confidential messages secrecy rate regions"

Connected through hyperedge HE-3 (induced by source paper "a comparison of superposition coding schemes"):
  with members:
    - "optimal achievable rates for interference networks with random codes"

Connected through hyperedge HE-4 (induced by source paper "achievability proof via output statistics of random binning"):
  with members:
    - "when is it possible to simulate a dmc channel from another"
    - "distributed channel synthesis"
    - "hybrid coding an interface for joint source channel coding and network communication"
    - "channel simulation via interactive communications"
    - "coordination via a relay"
    - "strongly secure communications over the two way wiretap channel"
    - "strong secrecy from channel resolvability"
    - "construction of slepian wolf source code and broadcast channel code based on hash property"

Connected through hyperedge HE-5 (induced by source paper "broadcast channels with confidential messages by randomness constrained stochastic encoder"):
  with members:
    - "secure multiplex coding with dependent and non uniform multiple messages"
    - "on secure communication with constrained randomization"
    - "wiretap channels implications of the more capable condition and cyclic shift symmetry"
    - "exponential decreasing rate of leaked information in universal random privacy amplification"
    - "capacity results for relay channels with confidential messages"
    - "capacity regions of two new classes of 2 receiver broadcast channels"
    - "secure multiplex coding to attain the channel capacity in wiretap channels"

Connected through hyperedge HE-6 (induced by source paper "secret key agreement with channel state information at the transmitter"):
  with members:
    - "secrecy via sources and channels"
    - "wiretap channel with causal state information"
    - "lecture notes on network information theory"
    - "fingerprints in the ether using the physical layer for wireless authentication"

Connected through hyperedge HE-7 (induced by source paper "a new method for variable elimination in systems of inequations"):
  with members:
    - "on the capacity of causal cognitive interference channel with delay"
    - "lecture notes on network information theory"
    - "gaussian interference channel capacity to within one bit"

Connected through hyperedge HE-8 (induced by source paper "security embedding codes"):
  with members:
    - "new results on multiple input multiple output broadcast channels with confidential messages"

Question: Please tell me which class the center node 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)