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 "a capacity achieving t pir scheme based on mds array codes"):
  Abstract: Suppose a database containing $M$ records is replicated in each of $N$ servers, and a user wants to privately retrieve one record by accessing the servers such that identity of the retrieved record is secret against any up to $T$ servers. A scheme designed for this purpose is called a $T$-private information retrieval ($T$-PIR) scheme. #R##N#In this paper we focus on the field size of $T$-PIR schemes. We design a generalcapacity-achieving $T$-PIR scheme whose queries are generated by using some {\rm MDS } array codes. It only requires field size $q\geq\sqrt[\ell]{N}$, where $\ell=\min\{t^{M-2},(n-t)^{M-2}\}$, $~t=T/{\rm gcd}(N,T)$,$~n=N/{\rm gcd}(N,T)$ and has the optimal sub-packetization $Nn^{M-2}$. Comparing with existing capacity-achieving $T$-PIR schemes, our scheme has the following advantage, that is, its field size monotonically decreases as the number of records $M$ grows. In particular, the binary field is sufficient for building a capacity-achieving T-PIR scheme as long as $M\geq 2+\lceil\log_\mu\log_2N\rceil$, where $\mu=\min\{t,n-t\}>1$.

Includes members:
  Member "an mds pir capacity achieving protocol for distributed storage using non mds linear codes":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "latent variable private information retrieval")
  Member "building capacity achieving pir schemes with optimal sub packetization over small fields":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "private information retrieval through wiretap channel ii privacy meets security")
  Member "a general private information retrieval scheme for mds coded databases with colluding servers":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "private set intersection a multi message symmetric private information retrieval perspective")
  Member "t private information retrieval schemes using transitive codes":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "towards practical private information retrieval from mds array codes")
  Member "the capacity of robust private information retrieval with colluding databases":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "gcsa codes with noise alignment for secure coded multi party batch matrix multiplication")
  Member "the capacity of symmetric private information retrieval":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "latent variable private information retrieval")
  Member "the capacity of private information retrieval":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "gcsa codes with noise alignment for secure coded multi party batch matrix multiplication")
  Member "the capacity of private information retrieval from coded databases":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "gcsa codes with noise alignment for secure coded multi party batch matrix multiplication")

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.IT(Information Theory)