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IIB-CPE: Inter and Intra Block Processing-Based Compressible Perceptual Encryption Method for Privacy-Preserving Deep

Ijaz Ahmad1, Seokjoo Shin1

  • 1Department of Computer Engineering, Chosun University, Gwangju 61452, Korea.

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|October 27, 2022
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Summary
This summary is machine-generated.

This study introduces Inter and Intra Block Processing for Compressible Perceptual Encryption (IIB-CPE), enhancing image privacy. IIB-CPE improves bitrate savings and image quality, enabling privacy-preserving deep learning.

Keywords:
JPEG compressionimage codingperceptual encryptionprivacy-preserving deep learning

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Area of Science:

  • Computer Science
  • Image Processing
  • Cryptography

Background:

  • Perceptual encryption (PE) protects visual data while allowing in-domain computation.
  • Existing block-based PE methods achieve compression but degrade quality and color information by using pseudo-grayscale representations.
  • Limitations in current PE methods restrict their applicability, particularly in preserving image fidelity and color.

Purpose of the Study:

  • To develop a novel compressible perceptual encryption method that overcomes the limitations of existing techniques.
  • To enhance image quality and compression efficiency in perceptual encryption.
  • To extend the application scope of perceptual encryption to privacy-preserving deep learning (PPDL).

Main Methods:

  • Proposed Inter and Intra Block Processing for Compressible PE (IIB-CPE).
  • IIB-CPE processes input as a color image using block-level inter and sub-block-level intra processing.
  • Intra block processing employs an inside-out geometric transformation for visual encryption of local details while preserving global content.

Main Results:

  • IIB-CPE achieves improved encryption efficiency through smaller block sizes without compromising compression performance.
  • The method offers 15% bitrate savings compared to existing PE methods.
  • IIB-CPE demonstrates better image quality than conventional PE techniques.

Conclusions:

  • IIB-CPE effectively addresses limitations of prior PE methods, enhancing both security and image fidelity.
  • The proposed method maintains compression efficiency while improving visual quality.
  • IIB-CPE's applicability is extended to privacy-preserving deep learning, showcasing its versatility.