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On the Storage-Communication Trade-Off in Graph-Based X-Secure T-Private Linear Computation.

Yueyang Liu1, Haobo Jia1, Zhuqing Jia1

  • 1School of Artificial Intelligence, Beijing University of Posts and Telecommunications, Beijing 100876, China.

Entropy (Basel, Switzerland)
|September 27, 2025
PubMed
Summary
This summary is machine-generated.

We introduce a novel scheme for graph-based X-secure T-private linear computation (GXSTPLC). This method achieves a storage-communication trade-off and can be transformed for quantum applications.

Keywords:
communication efficiencycross subspace alignmentlinear computationprivate information retrievalstorage efficiency

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Area of Science:

  • Information Theory
  • Computer Science
  • Quantum Computing

Background:

  • Distributed systems face challenges in secure data retrieval.
  • Existing methods for private linear computation lack efficiency in graph-based storage.

Purpose of the Study:

  • To propose an efficient scheme for graph-based X-secure T-private linear computation (GXSTPLC).
  • To enable a storage-communication trade-off in distributed systems.
  • To facilitate transformation into a quantum scheme for enhanced gains.

Main Methods:

  • Exploiting non-replicated storage codes.
  • Utilizing cross-subspace alignment null shaper for graph-based structures.
  • Leveraging N-Sum Box abstraction for quantum transformation.

Main Results:

  • An achievability scheme for GXSTPLC is proposed.
  • The scheme offers a storage-communication trade-off.
  • Direct transformation to a quantum scheme for superdense coding gain is enabled.

Conclusions:

  • The proposed scheme effectively addresses GXSTPLC challenges in graph-based storage.
  • The work introduces a novel approach for secure and private linear computation.
  • Future work can explore quantum enhancements for greater efficiency.