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 "noisy guesses"):
  Abstract: We consider the problem of guessing a random, finite-alphabet, secret $n$-vector, where the guesses are transmitted via a noisy channel. We provide a single-letter formula for the best achievable exponential growth rate of the $\rho$--th moment of the number of guesses, as a function of $n$. This formula exhibits a fairly clear insight concerning the penalty due to the noise. We describe two different randomized schemes that achieve the optimal guessing exponent. One of them is fully universal in the sense of being independent of source (that governs the vector to be guessed), the channel (that corrupts the guesses), and the moment power $\rho$. Interestingly, it turns out that, in general, the optimal guessing exponent function exhibits a phase transition when it is examined either as a function of the channel parameters, or as a function of $\rho$: as long as the channel is not too distant (in a certain sense to be defined precisely) from the identity channel (i.e., the clean channel), or equivalently, as long $\rho$ is larger than a certain critical value, $\rho_{\mbox{\tiny c}}$, there is no penalty at all in the guessing exponent, compared to the case of noiseless guessing.

Includes members:
  Member "guessing individual sequences generating randomized guesses using finite state machines":
    also connected through other hyperedges:
      (none)
  Member "universal randomized guessing with application to asynchronous decentralized brute force attacks":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "mismatched guesswork")
  Member "why botnets work distributed brute force attacks need no synchronization":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "mismatched guesswork")

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)