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: "dynamic traitor tracing for arbitrary alphabets divide and conquer"
  Abstract: We give a generic divide-and-conquer approach for constructing collusion-resistant probabilistic dynamic traitor tracing schemes with larger alphabets from schemes with smaller alphabets. This construction offers a linear tradeoff between the alphabet size and the codelength. In particular, we show that applying our results to the binary dynamic Tardos scheme of Laarhoven et al. leads to schemes that are shorter by a factor equal to half the alphabet size. Asymptotically, these codelengths correspond, up to a constant factor, to the fingerprinting capacity for static probabilistic schemes. This gives a hierarchy of probabilistic dynamic traitor tracing schemes, and bridges the gap between the low bandwidth, high codelength scheme of Laarhoven et al. and the high bandwidth, low codelength scheme of Fiat and Tassa.

Connected through hyperedge HE-1 (induced by source paper "asymptotics of fingerprinting and group testing capacity achieving log likelihood decoders"):
  with members:
    - "asymptotics of fingerprinting and group testing tight bounds from channel capacities"
    - "optimal symmetric tardos traitor tracing schemes"
    - "capacities and capacity achieving decoders for various fingerprinting games"
    - "enhanced blind decoding of tardos codes with new map based functions"
    - "dynamic traitor tracing schemes revisited"
    - "discrete distributions in the tardos scheme revisited"
    - "efficient probabilistic group testing based on traitor tracing"
    - "dynamic tardos traitor tracing schemes"

Connected through hyperedge HE-2 (induced by source paper "asymptotics of fingerprinting and group testing tight bounds from channel capacities"):
  with members:
    - "asymptotics of fingerprinting and group testing capacity achieving log likelihood decoders"
    - "limits on support recovery with probabilistic models an information theoretic framework"
    - "capacities and capacity achieving decoders for various fingerprinting games"
    - "near optimal stochastic threshold group testing"
    - "dynamic traitor tracing schemes revisited"
    - "the capacity of adaptive group testing"
    - "efficient probabilistic group testing based on traitor tracing"
    - "dynamic tardos traitor tracing schemes"

Connected through hyperedge HE-3 (induced by source paper "capacities and capacity achieving decoders for various fingerprinting games"):
  with members:
    - "optimal symmetric tardos traitor tracing schemes"
    - "dynamic traitor tracing schemes revisited"
    - "discrete distributions in the tardos scheme revisited"
    - "efficient probabilistic group testing based on traitor tracing"
    - "dynamic tardos traitor tracing schemes"
    - "on the saddle point solution and the large coalition asymptotics of fingerprinting games"
    - "non adaptive group testing explicit bounds and novel algorithms"
    - "asymptotic fingerprinting capacity for non binary alphabets"

Connected through hyperedge HE-4 (induced by source paper "efficient probabilistic group testing based on traitor tracing"):
  with members:
    - "optimal symmetric tardos traitor tracing schemes"
    - "near optimal stochastic threshold group testing"
    - "dynamic traitor tracing schemes revisited"
    - "the capacity of adaptive group testing"
    - "dynamic tardos traitor tracing schemes"
    - "on the saddle point solution and the large coalition asymptotics of fingerprinting games"
    - "adaptive group testing as channel coding with feedback"
    - "boolean compressed sensing and noisy group testing"

Connected through hyperedge HE-5 (induced by source paper "dynamic traitor tracing schemes revisited"):
  with members:
    - "optimal symmetric tardos traitor tracing schemes"
    - "discrete distributions in the tardos scheme revisited"
    - "efficient probabilistic group testing based on traitor tracing"
    - "dynamic tardos traitor tracing schemes"
    - "on the saddle point solution and the large coalition asymptotics of fingerprinting games"

Connected through hyperedge HE-6 (induced by source paper "discrete distributions in the tardos scheme revisited"):
  with members:
    - "optimal symmetric tardos traitor tracing schemes"
    - "dynamic tardos traitor tracing schemes"
    - "on the saddle point solution and the large coalition asymptotics of fingerprinting games"
    - "asymptotic fingerprinting capacity for non binary alphabets"

Connected through hyperedge HE-7 (induced by source paper "dynamic tardos traitor tracing schemes"):
  with members:
    - "optimal symmetric tardos traitor tracing schemes"
    - "tardos fingerprinting is better than we thought"

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.CR(Cryptography and Security)