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: "source channel secrecy with causal disclosure"
  Abstract: Imperfect secrecy in communication systems is investigated. Instead of using equivocation as a measure of secrecy, the distortion that an eavesdropper incurs in producing an estimate of the source sequence is examined. The communication system consists of a source and a broadcast (wiretap) channel, and lossless reproduction of the source sequence at the legitimate receiver is required. A key aspect of this model is that the eavesdropper's actions are allowed to depend on the past behavior of the system. Achievability results are obtained by studying the performance of source and channel coding operations separately, and then linking them together digitally. Although the problem addressed here has been solved when the secrecy resource is shared secret key, it is found that substituting secret key for a wiretap channel brings new insights and challenges: the notion of weak secrecy provides just as much distortion at the eavesdropper as strong secrecy, and revealing public messages freely is detrimental.

Connected through hyperedge HE-1 (induced by source paper "gaussian secure source coding and wyner s common information"):
  with members:
    - "an extremal inequality for long markov chains"
    - "secure coordination with a two sided helper"
    - "the lossy common information of correlated sources"
    - "wyner s common information generalizations and a new lossy source coding interpretation"
    - "a bit of secrecy for gaussian source compression"
    - "optimal equivocation in secrecy systems a special case of distortion based characterization"
    - "on secure source coding with side information at the encoder"
    - "distributed channel synthesis"

Connected through hyperedge HE-2 (induced by source paper "joint source channel secrecy using hybrid coding"):
  with members:
    - "rate distortion based physical layer secrecy with applications to multimode fiber"
    - "a rate distortion based secrecy system with side information at the decoders"
    - "the likelihood encoder for lossy source compression"
    - "the likelihood encoder for source coding"
    - "distributed channel synthesis"
    - "rate distortion theory for secrecy systems"
    - "hybrid coding an interface for joint source channel coding and network communication"
    - "secrecy is cheap if the adversary must reconstruct"

Connected through hyperedge HE-3 (induced by source paper "rate distortion based physical layer secrecy with applications to multimode fiber"):
  with members:
    - "rate distortion theory for secrecy systems"
    - "secrecy is cheap if the adversary must reconstruct"
    - "multiple input multiple output gaussian broadcast channels with common and confidential messages"
    - "a framework for partial secrecy"
    - "the secrecy capacity of the mimo wiretap channel"

Connected through hyperedge HE-4 (induced by source paper "a bit of secrecy for gaussian source compression"):
  with members:
    - "optimal equivocation in secrecy systems a special case of distortion based characterization"
    - "rate distortion theory for secrecy systems"
    - "secrecy is cheap if the adversary must reconstruct"
    - "using a secret key to foil an eavesdropper"
    - "a framework for partial secrecy"

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)