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 "privacy in index coding improved bounds and coding schemes"):
  Abstract: It was recently observed in [1], that in index coding, learning the coding matrix used by the server can pose privacy concerns: curious clients can extract information about the requests and side information of other clients. One approach to mitigate such concerns is the use of k-limited-access schemes [1], that restrict each client to learn only part of the index coding matrix, and in particular, at most  $k$  rows. These schemes transform a linear index coding matrix of rank  $T$  to an alternate one, such that each client needs to learn at most  $k$  of the coding matrix rows to decode its requested message. This paper analyzes k-limited-access schemes. First, a worst-case scenario, where the total number of clients  $n$  is  $2^{T}-1$  is studied. For this case, a novel construction of the coding matrix is provided and shown to be order-optimal in the number of transmissions. Then, the case of a general  $n$  is considered and two different schemes are designed and analytically and numerically assessed in their performance. It is shown that these schemes perform better than the one designed for the case  $n=2^{T}-1$ .

Includes members:
  Member "preserving privacy while broadcasting k limited access schemes":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "on locally decodable index codes")
  Member "private broadcasting an index coding approach":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "subpacketization in coded caching with demand privacy")
  Member "the capacity of private information retrieval from coded databases":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "gcsa codes with noise alignment for secure coded multi party batch matrix multiplication")
  Member "the oblivious transfer capacity of the wiretapped binary erasure channel":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "preserving privacy while broadcasting k limited access schemes")
  Member "on the security of index coding with side information":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "secure decentralized pliable index coding")

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)