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: "reliable and secure multishot network coding using linearized reed solomon codes"
  Abstract: Multishot network coding is considered in a worst-case adversarial setting in which an omniscient adversary with unbounded computational resources may inject erroneous packets in up to    $t$    links, erase up to    $\rho $    packets, and wire-tap up to    $\mu $    links, all throughout    $\ell $    shots of a linearly-coded network. Assuming no knowledge of the underlying linear network code (in particular, the network topology and underlying linear code may be random and change with time), a coding scheme achieving zero-error communication and perfect secrecy is obtained based on linearized Reed-Solomon codes. The scheme achieves the maximum possible secret message size of    $\ell n^\prime - 2t - \rho - \mu $    packets for coherent communication, where    $n^\prime $    is the number of outgoing links at the source, for any packet length    $m \geq n^\prime $    (largest possible range). By lifting this construction, coding schemes for non-coherent communication are obtained with information rates close to optimal for practical instances. The required field size is    $q^{m} $   , where    $q > \ell $   , thus    $q^{m} \approx \ell ^{n^\prime } $   , which is always smaller than that of a Gabidulin code tailored for    $\ell $    shots, which would be at least    $2^{\ell n^\prime } $   . A Welch-Berlekamp sum-rank decoding algorithm for linearized Reed-Solomon codes is provided, having quadratic complexity in the total length    $n = \ell n^\prime $   , and which can be adapted to handle not only errors but also erasures, wire-tap observations and non-coherent communication. Combined with the obtained field size, the given decoding complexity is of    $\mathcal {O}(n^{\prime 4} \ell ^{2} \log (\ell)^{2}) $    operations in    $\mathbb {F}_{2} $   , whereas the most efficient known decoding algorithm for a Gabidulin code has a complexity of    $\mathcal {O}(n^{\prime 3.69} \ell ^{3.69} \log (\ell)^{2}) $    operations in    $\mathbb {F}_{2} $   , assuming a multiplication in a finite field    $\mathbb {F} $    costs about    $\log (|\mathbb {F}|)^{2} $    operations in    $\mathbb {F}_{2} $   .

Connected through hyperedge HE-1 (induced by source paper "locally repairable convolutional codes with sliding window repair"):
  with members:
    - "universal and dynamic locally repairable codes with maximal recoverability via sum rank codes"
    - "locally repairable codes with unequal local erasure correction"
    - "skew and linearized reed solomon codes and maximum sum rank distance codes over any division ring"
    - "bounds and constructions of codes with multiple localities"
    - "codes with unequal locality"
    - "superregular matrices and applications to convolutional codes"
    - "convolutional codes in rank metric with application to random network coding"
    - "convolutional codes with maximum column sum rank for network streaming"

Connected through hyperedge HE-2 (induced by source paper "on some automorphisms of rational functions and their applications in rank metric codes"):
  with members:
    - "low rank parity check codes new decoding algorithms and applications to cryptography"
    - "maximal ferrers diagram codes constructions and genericity considerations"
    - "on the genericity of maximum rank distance and gabidulin codes"
    - "skew and linearized reed solomon codes and maximum sum rank distance codes over any division ring"
    - "new criteria for mrd and gabidulin codes and some rank metric code constructions"
    - "a singleton bound for generalized ferrers diagram rank metric codes"
    - "convolutional codes with maximum column sum rank for network streaming"
    - "subspace codes from ferrers diagrams"

Connected through hyperedge HE-3 (induced by source paper "hamming and simplex codes for the sum rank metric"):
  with members:
    - "universal and dynamic locally repairable codes with maximal recoverability via sum rank codes"
    - "optimal locally repairable and secure codes for distributed storage systems"
    - "partial spreads in random network coding"
    - "on the locality of codeword symbols"
    - "multishot codes for network coding using rank metric codes"
    - "coding for errors and erasures in random network coding"
    - "properties of codes in rank metric"

Connected through hyperedge HE-4 (induced by source paper "universal and dynamic locally repairable codes with maximal recoverability via sum rank codes"):
  with members:
    - "maximally recoverable codes with hierarchical locality"
    - "extended integrated interleaved codes over any field with applications to locally recoverable codes"
    - "random construction of partial mds codes"
    - "how long can optimal locally repairable codes be"
    - "constructions of maximally recoverable local reconstruction codes via function fields"
    - "locally repairable codes with unequal local erasure correction"
    - "optimal locally repairable codes of distance 3 and 4 via cyclic codes"
    - "skew and linearized reed solomon codes and maximum sum rank distance codes over any division ring"

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)