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 "discrete distributions in the tardos scheme revisited"):
  Abstract: The Tardos scheme is a well-known traitor tracing scheme to protect copyrighted content against collusion attacks. The original scheme contained some suboptimal design choices, such as the score function and the distribution function used for generating the biases. Skoric et al. previously showed that a symbol-symmetric score function leads to shorter codes, while Nuida et al. obtained the optimal distribution functions for arbitrary coalition sizes. Later, Nuida et al. showed that combining these results leads to even shorter codes when the coalition size is small. We extend their analysis to the case of large coalitions and prove that these optimal distributions converge to the arcsine distribution, thus showing that the arcsine distribution is asymptotically optimal in the symmetric Tardos scheme. We also present a new, practical alternative to the discrete distributions of Nuida et al. and give a comparison of the estimated lengths of the fingerprinting codes for each of these distributions.

Includes members:
  Member "optimal symmetric tardos traitor tracing schemes":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "nearest neighbor decoding for tardos fingerprinting codes")
  Member "dynamic tardos traitor tracing schemes":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "nearest neighbor decoding for tardos fingerprinting codes")
  Member "on the saddle point solution and the large coalition asymptotics of fingerprinting games":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "asymptotics of fingerprinting and group testing capacity achieving log likelihood decoders")
  Member "dynamic traitor tracing for arbitrary alphabets divide and conquer":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "asymptotics of fingerprinting and group testing capacity achieving log likelihood decoders")
  Member "asymptotic fingerprinting capacity for non binary alphabets":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "asymptotics of fingerprinting and group testing capacity achieving log likelihood decoders")

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.CR(Cryptography and Security)