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 "secrecy in cascade networks"):
  Abstract: We consider a cascade network where a sequence of nodes each send a message to their downstream neighbor to enable coordination, the first node having access to an information signal. An adversary also receives all of the communication as well as additional side-information. The performance of the system is measured by a payoff function evaluated on actions produced at each of the nodes, including the adversary. The challenge is to effectively use a secret key to infuse some level of privacy into the encoding, in order thwart the adversary's attempt to reduce the payoff. We obtain information-theoretic inner and outer bounds on performance, and give examples where they are tight. From these bounds, we also derive the optimal equivocation for this setting as a special case.

Includes members:
  Member "secure cascade channel synthesis":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "coordination through shared randomness")
  Member "optimal equivocation in secrecy systems a special case of distortion based characterization":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "gaussian secure source coding and wyner s common information")
  Member "the likelihood encoder for source coding":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "the likelihood encoder for lossy compression")
  Member "distributed channel synthesis":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "gaussian approximation of quantization error for estimation from compressed data")
  Member "rate distortion theory for secrecy systems":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "privacy aware distributed hypothesis testing")
  Member "secrecy is cheap if the adversary must reconstruct":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "a large deviations approach to secure lossy compression")
  Member "multiterminal source coding under logarithmic loss":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "on the information bottleneck problems models connections applications and information theoretic views")
  Member "multiterminal source coding with an entropy based distortion measure":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "vector gaussian ceo problem under logarithmic loss")

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)