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: "multi user guesswork and brute force security"
  Abstract: The guesswork problem was originally motivated by a desire to quantify computational security for single user systems. Leveraging recent results from its analysis, we extend the remit and utility of the framework to the quantification of the computational security of multi-user systems. In particular, assume that    $V$    users independently select strings stochastically from a finite, but potentially large, list. An inquisitor who does not know which strings have been selected wishes to identify    $U$    of them. The inquisitor knows the selection probabilities of each user and is equipped with a method that enables the testing of each (user, string) pair, one at a time, for whether that string had been selected by that user. Here, we establish that, unless    $U=V$   , there is no general strategy that minimizes the distribution of the number of guesses, but in the asymptote as the strings become long we prove the following: by construction, there is an asymptotically optimal class of strategies; the number of guesses required in an asymptotically optimal strategy satisfies a large deviation principle with a rate function, which is not necessarily convex, that can be determined from the rate functions of optimally guessing individual users’ strings; if all users’ selection statistics are identical, the exponential growth rate of the average guesswork as the string-length increases is determined by the specific Renyi entropy of the string-source with parameter    $(V-U+1)/(V-U+2)$   , generalizing the known    $V=U=1$    case; and that the Shannon entropy of the source is a lower bound on the average guesswork growth rate for all    $U$    and    $V$   , thus providing a bound on computational security for multi-user systems. Examples are presented to illustrate these results and their ramifications for systems design.

Connected through hyperedge HE-1 (induced by source paper "mismatched guesswork"):
  with members:
    - "universal randomized guessing with application to asynchronous decentralized brute force attacks"
    - "why botnets work distributed brute force attacks need no synchronization"
    - "a characterization of guesswork on swiftly tilting curves"
    - "centralized vs decentralized multi agent guesswork"
    - "guesswork subject to a total entropy budget"
    - "list decoding random coding exponents and expurgated exponents"
    - "asymptotics and non asymptotics for universal fixed to variable source coding"
    - "erasure list random coding error exponents are not universally achievable"

Connected through hyperedge HE-2 (induced by source paper "capacity achieving guessing random additive noise decoding"):
  with members:
    - "on the origin of polar coding"
    - "the random coding bound is tight for the average linear code or lattice"
    - "guesswork large deviations and shannon entropy"
    - "brute force searching the typical set and guesswork"
    - "guessing a password over a wireless channel on the effect of noise non uniformity"
    - "frames in outdoor 802 11 wlans provide a hybrid binary symmetric packet erasure channel"
    - "guessing revisited a large deviations approach"
    - "channel polarization a method for constructing capacity achieving codes for symmetric binary input memoryless channels"

Connected through hyperedge HE-3 (induced by source paper "privacy against brute force inference attacks"):
  with members:
    - "estimation efficiency under privacy constraints"
    - "a tunable measure for information leakage"
    - "privacy utility tradeoffs under constrained data release mechanisms"
    - "from the information bottleneck to the privacy funnel"
    - "privacy against statistical inference"
    - "guessing revisited a large deviations approach"

Connected through hyperedge HE-4 (induced by source paper "guessing with a bit of help"):
  with members:
    - "reducing guesswork via an unreliable oracle"
    - "on the optimal boolean function for prediction under quadratic loss"
    - "password cracking the effect of hash function bias on the average guesswork"
    - "on the entropy of a noisy function"
    - "remarks on the most informative function conjecture at fixed mean"
    - "an improved upper bound for the most informative boolean function conjecture"
    - "analysis of boolean functions"
    - "strong data processing inequalities and phi sobolev inequalities for discrete channels"

Connected through hyperedge HE-5 (induced by source paper "universal randomized guessing with application to asynchronous decentralized brute force attacks"):
  with members:
    - "why botnets work distributed brute force attacks need no synchronization"
    - "centralized vs decentralized multi agent guesswork"
    - "guesswork subject to a total entropy budget"
    - "guessing attacks on distributed storage systems"
    - "asymptotics and non asymptotics for universal fixed to variable source coding"
    - "guesswork large deviations and shannon entropy"
    - "guessing a password over a wireless channel on the effect of noise non uniformity"
    - "investigating the distribution of password choices"

Connected through hyperedge HE-6 (induced by source paper "on the conditional smooth renyi entropy and its applications in guessing and source coding"):
  with members:
    - "non asymptotic fundamental limits of guessing subject to distortion"
    - "a characterization of guesswork on swiftly tilting curves"
    - "non asymptotic and asymptotic fundamental limits of guessing subject to distortion"
    - "on the smooth renyi entropy and variable length source coding allowing errors"
    - "variable length compression allowing errors extended"
    - "variable length compression allowing errors"
    - "guesswork large deviations and shannon entropy"
    - "guessing revisited a large deviations approach"

Connected through hyperedge HE-7 (induced by source paper "why botnets work distributed brute force attacks need no synchronization"):
  with members:
    - "a characterization of guesswork on swiftly tilting curves"
    - "centralized vs decentralized multi agent guesswork"
    - "guesswork subject to a total entropy budget"
    - "guessing attacks on distributed storage systems"
    - "asymptotics and non asymptotics for universal fixed to variable source coding"
    - "guesswork large deviations and shannon entropy"
    - "guessing a password over a wireless channel on the effect of noise non uniformity"
    - "guessing revisited a large deviations approach"

Connected through hyperedge HE-8 (induced by source paper "a characterization of guesswork on swiftly tilting curves"):
  with members:
    - "list decoding random coding exponents and expurgated exponents"
    - "asymptotics and non asymptotics for universal fixed to variable source coding"
    - "guesswork large deviations and shannon entropy"
    - "brute force searching the typical set and guesswork"
    - "guessing a password over a wireless channel on the effect of noise non uniformity"
    - "guessing revisited a large deviations approach"
    - "guessing under source uncertainty"

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)