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 "separate random number generation from correlated sources"):
  Abstract: This work studies the problem of separate random number generation from correlated general sources with side information at the tester under the criterion of statistical distance. Tight one-shot lower and upper performance bounds are obtained using the random-bin approach. A refined analysis is further performed for two important random-bin maps. One is the pure-random-bin map that is uniformly distributed over the set of all maps (with the same domain and codomain). The other is the equal-random-bin map that is uniformly distributed over the set of all surjective maps that induce an equal or quasi-equal partition of the domain. Both of them are proved to have a doubly-exponential concentration of the performance of their sample maps. As an application, an open and transparent lottery scheme, using a random number generator on a public data source, is proposed to solve the social problem of scarce resource allocation. The core of the proposed framework of lottery algorithms is a permutation, a good rateless randomness extractor, whose existence is confirmed by the theoretical performance of equal-random-bin maps. This extractor, together with other important details of the scheme, ensures that the lottery scheme is immune to all kinds of fraud under some reasonable assumptions.

Includes members:
  Member "non asymptotic output statistics of random binning and its applications":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "physical layer security in the finite blocklength regime over fading channels")
  Member "achievability proof via output statistics of random binning":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "biometric and physical identifiers with correlated noise for controllable private authentication")

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)