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Distributed Identity Authentication with Lenstra-Lenstra-Lovász Algorithm-Ciphertext Policy Attribute-Based

Qi Yuan1, Hao Yuan1, Jing Zhao1

  • 1Faculty of Communication and Electronic Engineering, Qiqihar University, Qiqihar 161000, China.

Entropy (Basel, Switzerland)
|September 27, 2024
PubMed
Summary
This summary is machine-generated.

This study introduces a quantum-resistant attribute-based encryption (ABE) scheme using lattice-based cryptography. The improved method enhances security and efficiency by optimizing random value generation and reducing computational overhead.

Keywords:
Lenstra–Lenstra–Lovász lattice reduction algorithmencryption of policy attributesidentity authenticationlattice cryptography

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Area of Science:

  • Cryptography
  • Quantum Computing Security

Background:

  • Traditional attribute-based encryption (ABE) faces challenges in the quantum era.
  • Single-authority ABE systems present a single point of failure.
  • Quantum computing necessitates the development of quantum-resistant cryptographic solutions.

Purpose of the Study:

  • To propose an improved lattice-based, quantum-resistant identity authentication and policy attribute encryption scheme.
  • To address the single point of failure issue in traditional ABE.
  • To enhance the efficiency and security of ABE in the quantum domain.

Main Methods:

  • Optimized random value generation using adjusted Gaussian sampling parameters.
  • Efficient attribute processing based on shared nature during key generation.
  • Application of the Lenstra-Lenstra-Lovász (LLL) lattice reduction algorithm for decryption.

Main Results:

  • Improved performance through optimized random value generation.
  • Reduced computational overhead for the authorization authority.
  • Decreased computational cost in decryption via LLL algorithm for linear space checks.
  • Enhanced security and efficiency compared to existing schemes.

Conclusions:

  • The proposed lattice-based ABE scheme offers a viable quantum-resistant solution.
  • The optimizations in random value generation and attribute processing improve overall system performance.
  • The integration of LLL algorithm significantly reduces decryption computational costs, enhancing practical applicability.