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: "saddle point solution of the fingerprinting capacity game under the marking assumption"
  Abstract: We study a fingerprinting game in which the collusion channel is unknown. The encoder embeds fingerprints into a host sequence and provides the decoder with the capability to trace back pirated copies to the colluders.

Connected through hyperedge HE-1 (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-2 (induced by source paper "optimal sequential fingerprinting wald vs tardos"):
  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"
    - "interactive fingerprinting codes and the hardness of preventing false discovery"
    - "enhanced blind decoding of tardos codes with new map based functions"
    - "dynamic traitor tracing schemes revisited"
    - "discrete distributions in the tardos scheme revisited"
    - "fingerprinting codes and the price of approximate differential privacy"

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"
    - "dynamic traitor tracing for arbitrary alphabets divide and conquer"

Connected through hyperedge HE-4 (induced by source paper "optimal symmetric tardos traitor tracing schemes"):
  with members:
    - "tardos fingerprinting is better than we thought"

Connected through hyperedge HE-5 (induced by source paper "on the saddle point solution and the large coalition asymptotics of fingerprinting games"):
  with members:
    - "worst case attacks against binary probabilistic traitor tracing codes"
    - "tardos fingerprinting is better than we thought"

Connected through hyperedge HE-6 (induced by source paper "asymptotically false positive maximizing attack on non binary tardos codes"):
  with members:
    - "universal fingerprinting capacity and random coding exponents"
    - "tardos fingerprinting is better than we thought"

Connected through hyperedge HE-7 (induced by source paper "asymptotic fingerprinting capacity for non binary alphabets"):
  with members:
    - "universal fingerprinting capacity and random coding exponents"
    - "tardos fingerprinting is better than we thought"

Connected through hyperedge HE-8 (induced by source paper "worst case attacks against binary probabilistic traitor tracing codes"):
  with members:
    - "universal fingerprinting capacity and random coding exponents"
    - "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.IT(Information Theory)