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Provably Secure Symmetric Private Information Retrieval with Quantum Cryptography.

Wen Yu Kon1, Charles Ci Wen Lim1,2

  • 1Department of Electrical & Computer Engineering, National University of Singapore, Singapore 119077, Singapore.

Entropy (Basel, Switzerland)
|January 5, 2021
PubMed
Summary

This study introduces quantum key distribution (QKD) for practical symmetric private information retrieval (SPIR), enhancing database privacy and secure communication. QKD overcomes limitations of classical methods, enabling secure data access with current technology.

Keywords:
information theoretic securityquantum cryptographyquantum key distributionsymmetric private information retrieval

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Area of Science:

  • Quantum Information Science
  • Cryptography
  • Computer Science

Background:

  • Private Information Retrieval (PIR) protocols protect user query privacy.
  • Symmetric PIR (SPIR) further enhances privacy by protecting database entries.
  • Classical SPIR solutions require impractical long secret keys and shared randomness.

Purpose of the Study:

  • To propose a practical implementation of SPIR using Quantum Key Distribution (QKD).
  • To demonstrate how QKD can provide secure communication and shared randomness for SPIR.
  • To ensure the security of SPIR against external eavesdroppers.

Main Methods:

  • Utilizing measurement device-independent QKD (MDI-QKD) for key generation.
  • Developing a classical-quantum system for a two-database SPIR protocol.
  • Proving the security of the QKD-enhanced SPIR protocol.

Main Results:

  • QKD successfully maintains the security of the SPIR protocol.
  • The proposed system is secure against external eavesdroppers.
  • Key rate calculations show feasibility for metropolitan-level implementation with current QKD technology.

Conclusions:

  • QKD offers a practical solution for unconditionally secure SPIR.
  • The integration of QKD addresses the limitations of classical SPIR protocols.
  • This research paves the way for real-world applications of secure private information retrieval.