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: "connecting multiple unicast and network error correction reduction and unachievability"
  Abstract: We show that solving a multiple-unicast network coding problem can be reduced to solving a single-unicast network error correction problem, where an adversary may jam at most a single edge in the network. Specifically, we present an efficient reduction that maps a multiple-unicast network coding instance to a network error correction instance while preserving feasibility. The reduction holds for both the zero probability of error model and the vanishing probability of error model. Previous reductions are restricted to the zero-error case. As an application of the reduction, we present a constructive example showing that the single-unicast network error correction capacity may not be achievable, a result of separate interest.

Connected through hyperedge HE-1 (induced by source paper "arbitrarily varying networks capacity achieving computationally efficient codes"):
  with members:
    - "coding against a limited view adversary the effect of causality and feedback"
    - "routing for security in networks with adversarial nodes"
    - "polytope codes against adversaries in networks"
    - "network codes resilient to jamming and eavesdropping"
    - "network error correction with unequal link capacities"
    - "adversarial models and resilient schemes for network coding"
    - "coding for errors and erasures in random network coding"

Connected through hyperedge HE-2 (induced by source paper "a numerical study on the wiretap network with a simple network topology"):
  with members:
    - "characterizing the rate region of the 4 3 3 exact repair regenerating codes"
    - "on secure network coding with nonuniform or restricted wiretap sets"
    - "on secure network coding with uniform wiretap sets"
    - "network coding capacity regions via entropy functions"
    - "performance bounds on a wiretap network with arbitrary wiretap sets"
    - "linear rank inequalities on five or more variables"

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)