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 schemes revisited"
  Abstract: We revisit recent results from the area of collusion-resistant traitor tracing, and show how they can be combined and improved to obtain more efficient dynamic traitor tracing schemes. In particular, we show how the dynamic Tardos scheme of Laarhoven et al. can be combined with the optimized score functions of Oosterwijk et al. to trace coalitions much faster. If the attack strategy is known, in many cases the order of the code length goes down from quadratic to linear in the number of colluders, while if the attack is not known, we show how the interleaving defense may be used to catch all colluders about twice as fast as in the dynamic Tardos scheme. Some of these results also apply to the static traitor tracing setting where the attack strategy is known in advance, and to group testing.

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"
    - "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-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"
    - "the capacity of adaptive group testing"
    - "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-3 (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"
    - "discrete distributions in the tardos scheme revisited"
    - "fingerprinting codes and the price of approximate differential privacy"
    - "efficient probabilistic group testing based on traitor tracing"

Connected through hyperedge HE-4 (induced by source paper "capacities and capacity achieving decoders for various fingerprinting games"):
  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"
    - "non adaptive group testing explicit bounds and novel algorithms"
    - "dynamic traitor tracing for arbitrary alphabets divide and conquer"
    - "asymptotic fingerprinting capacity for non binary alphabets"

Connected through hyperedge HE-5 (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"
    - "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"
    - "dynamic traitor tracing for arbitrary alphabets divide and conquer"

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)