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 "secret key agreement from correlated data with no prior information"):
  Abstract: A fundamental question that has been studied in cryptography and in information theory is whether two parties can communicate confidentially using exclusively an open channel. We consider the model in which the two parties hold inputs that are correlated in a certain sense. This model has been studied extensively in information theory, and communication protocols have been designed which exploit the correlation to extract from the inputs a shared secret key. However, all the existing protocols are not universal in the sense that they require that the two parties also know some attributes of the correlation. In other words, they require that each party knows something about the other party's input. We present a protocol that does not require any prior additional information. It uses space-bounded Kolmogorov complexity to measure correlation and it allows the two legal parties to obtain a common key that looks random to an eavesdropper that observes the communication and is restricted to use a bounded amount of space for the attack. Thus the protocol achieves complexity-theoretical security, but it does not use any unproven result from computational complexity. On the negative side, the protocol is not efficient in the sense that the computation of the two legal parties uses more space than the space allowed to the adversary.

Includes members:
  Member "an operational characterization of mutual information in algorithmic information theory":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "on a conditional inequality in kolmogorov complexity and its applications in communication complexity")
  Member "on slepian wolf theorem with interaction":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "one shot variable length secret key agreement approaching mutual information")
  Member "kolmogorov complexity version of slepian wolf coding":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "universal almost optimal compression and slepian wolf coding in probabilistic polynomial time")
  Member "linear list approximation for short programs or the power of a few random bits":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "universal almost optimal compression and slepian wolf coding in probabilistic polynomial time")
  Member "information equals amortized communication":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "communication for generating correlation a unifying survey")
  Member "variations on muchnik s conditional complexity theorem":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "universal almost optimal compression and slepian wolf coding in probabilistic polynomial time")

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)