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Authenticated Public Key Elliptic Curve Based on Deep Convolutional Neural Network for Cybersecurity Image Encryption

Esam A A Hagras1, Saad Aldosary2, Haitham Khaled3

  • 1Faculty of Engineering, Delta University for Science and Technology, Gamasa 35712, Egypt.

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|July 29, 2023
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Summary

This study introduces a novel cybersecurity image encryption method using an authenticated public key elliptic curve deep convolutional neural network (APK-EC-DCNN). The technique enhances data privacy and security through advanced cryptographic and chaotic mapping methods.

Keywords:
cybersecuritydeep convolutional neural networkimage encryption

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Area of Science:

  • Computer Science
  • Cryptography
  • Image Processing

Background:

  • Growing demand for robust cybersecurity solutions to protect information flow and data privacy.
  • Need for advanced encryption techniques capable of handling complex data like images.

Purpose of the Study:

  • To propose a novel authenticated public key elliptic curve deep convolutional neural network (APK-EC-DCNN) for cybersecurity image encryption.
  • To enhance data authenticity, confidentiality, and robustness against attacks.

Main Methods:

  • Utilizing elliptic curve Diffie-Hellman key exchange (EC-DHKE) for secure session key generation.
  • Employing a 3D Quantum Chaotic Logistic Map (3D QCLM) for high-level security and chaotic behavior.
  • Integrating a secure hash function with DCNN and 3D QCLM outputs for an authenticated expansion diffusion matrix (AEDM).
  • Applying partial frequency domain encryption (PFDE) using discrete wavelet transform for robustness and speed.

Main Results:

  • The proposed APK-EC-DCNN encryption algorithm demonstrates high performance in terms of image quality and security.
  • The encryption method shows significant robustness against noise and signal-processing attacks.
  • Achieved state-of-the-art performance compared to existing encryption techniques.

Conclusions:

  • The developed APK-EC-DCNN method offers a secure and efficient solution for image encryption in cybersecurity applications.
  • The combination of elliptic curve cryptography, deep learning, and chaotic maps provides a strong defense mechanism.
  • The algorithm successfully balances security, quality, and robustness for practical implementation.