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: "secure erasure codes with partial decodability"
  Abstract: The MDS property (aka the $k$-out-of-$n$ property) requires that if a file is split into several symbols and subsequently encoded into $n$ coded symbols, each being stored in one storage node of a distributed storage system (DSS), then an user can recover the file by accessing any $k$ nodes. We study the so-called $p$-decodable $\mu$-secure erasure coding scheme $(1 \leq p \leq k - \mu, 0 \leq \mu < k, p | (k-\mu))$, which satisfies the MDS property and the following additional properties: #R##N#(P1) strongly secure up to a threshold: an adversary which eavesdrops at most $\mu$ storage nodes gains no information (in Shannon's sense) about the stored file, #R##N#(P2) partially decodable: a legitimate user can recover a subset of $p$ file symbols by accessing some $\mu + p$ storage nodes. #R##N#The scheme is perfectly $p$-decodable $\mu$-secure if it satisfies the following additional property: #R##N#(P3) weakly secure up to a threshold: an adversary which eavesdrops more than $\mu$ but less than $\mu+p$ storage nodes cannot reconstruct any part of the file. #R##N#Most of the related work in the literature only focused on the case $p = k - \mu$. In other words, no partial decodability is provided: an user cannot retrieve any part of the file by accessing less than $k$ nodes. #R##N#We provide an explicit construction of $p$-decodable $\mu$-secure coding schemes over small fields for all $\mu$ and $p$. That construction also produces perfectly $p$-decodable $\mu$-secure schemes over small fields when $p = 1$ (for every $\mu$), and when $\mu = 0, 1$ (for every $p$). We establish that perfect schemes exist over \emph{sufficiently large} fields for almost all $\mu$ and $p$.

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)