Parallel Binary Image Cryptosystem Via Spiking Neural Networks Variants.

Journal: International journal of neural systems
Published Date: Feb 26, 2021

Abstract

Due to the inefficiency of multiple binary images encryption, a parallel binary image encryption framework based on the typical variants of spiking neural networks, spiking neural P (SNP) systems is proposed in this paper. More specifically, the two basic units in the proposed image cryptosystem, the permutation unit and the diffusion unit, are designed through SNP systems with multiple channels and polarizations (SNP-MCP systems), and SNP systems with astrocyte-like control (SNP-ALC systems), respectively. Different from the serial computing of the traditional image permutation/diffusion unit, SNP-MCP-based permutation/SNP-ALC-based diffusion unit can realize parallel computing through the parallel use of rules inside the neurons. Theoretical analysis results confirm the high efficiency of the binary image proposed cryptosystem. Security analysis experiments demonstrate the security of the proposed cryptosystem.

Authors

  • Mingzhe Liu
    School of Computer Science and Software Engineering, University of Science and Technology Liaoning, Anshan, China.
  • Feixiang Zhao
    State Key Laboratory of Geohazard Prevention and Geoenvironment Protection, Chengdu University of Technology, Chengdu 610051, P. R. China.
  • Xin Jiang
    Department of Cardiology, Shaanxi Provincial People's Hospital, Xi'an, People's Republic of China.
  • Hong Zhang
    Department of Anesthesiology and Operation, The First Hospital of Lanzhou University, Lanzhou, Gansu, China.
  • Helen Zhou
    School of Engineering, Manukau Institute of Technology, Auckland 1150, New Zealand.

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