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: "two level fingerprinting codes"
  Abstract: We introduce the notion of two-level fingerprinting and traceability codes. In this setting, the users are organized in a hierarchical manner by classifying them into various groups; for instance, by dividing the distribution area into several geographic regions, and collecting users from the same region into one group. Two-level fingerprinting and traceability codes have the following property: As in traditional (one-level) codes, when given an illegal copy produced by a coalition of users, the decoder identifies one of the guilty users if the coalition size is less than a certain threshold $t$. Moreover, even when the coalition is of a larger size $s$ $(> t)$, the decoder still provides partial information by tracing one of the groups containing a guilty user. #R##N#We establish sufficient conditions for a code to possess the two-level traceability property. In addition, we also provide constructions for two-level fingerprinting codes and characterize the corresponding set of achievable rates.

Connected through hyperedge HE-1 (induced by source paper "signature codes for weighted binary adder channel and multimedia fingerprinting"):
  with members:
    - "codes with the identifiable parent property for multimedia fingerprinting"
    - "probabilistic existence results for separable codes"
    - "lectures on designing screening experiments"
    - "strongly separable codes"

Connected through hyperedge HE-2 (induced by source paper "universal fingerprinting capacity and random coding exponents"):
  with members:
    - "saddle point solution of the fingerprinting capacity game under the marking assumption"
    - "worst case attacks against binary probabilistic traitor tracing codes"
    - "on the fingerprinting capacity under the marking assumption"
    - "capacity and random coding exponents for channel coding with side information"

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)