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Data Acquisition Protocol for Determining Embedded Sensitivity Functions
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Quantum optimized hierarchical chunk encoding with robust embedding for perceptual integrity and compression tolerant

G Suresh1, J Arun Kumar2, Vivek Karthick Perumal3

  • 1Department of Artificial Intelligence and Machine Learning, Panimalar Engineering College, Chennai, India. gsuresh.aiml@panimalar.ac.in.

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A new Quantum-Optimized Hierarchical Chunk Encoding (QHCE) model improves image watermarking robustness and visual fidelity. This quantum-inspired approach enhances security for multimedia data against unauthorized access and manipulation.

Keywords:
Compression-tolerant watermarkingHierarchical chunk encodingImage protectionQuantum-optimized embeddingSecure data embeddingVisual integrity

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Area of Science:

  • Computer Science
  • Information Security
  • Quantum Computing

Background:

  • Multimedia platforms face increased threats like unauthorized access and data manipulation.
  • Classical watermarking methods lack robustness against compression and adversarial attacks.
  • Existing techniques suffer from low imperceptibility or high computational cost, limiting real-time applications.

Purpose of the Study:

  • To propose a novel Quantum-Optimized Hierarchical Chunk Encoding (QHCE) model for perceptually adaptive and compression-sensitive image watermarking.
  • To enhance robustness, imperceptibility, and efficiency in digital image watermarking.
  • To address the limitations of traditional watermarking techniques in adversarial environments.

Main Methods:

  • Image partitioning using entropy-based quadtree partitioning and saliency-based region selection.
  • Transform-domain watermark embedding utilizing multi-layers Discrete Wavelet Transform (DWT).
  • Quantum Genetic Algorithm (QGA) for optimizing embedding parameters (location, band, strength) to balance robustness and visual fidelity.

Main Results:

  • Achieved high performance metrics: average PSNR of 57.8 dB, SSIM of 0.997, 0.00% Bit Error Rate (BER), and 100% extraction accuracy at JPEG Quality Factor (QF) ≥ 70.
  • Demonstrated a 19% increase in payload capacity and a 25% reduction in runtime compared to non-optimized baselines.
  • Integrity verification reached 99.95% accuracy using SHA-256 and Hamming distance analysis.

Conclusions:

  • The QHCE model offers a scalable, secure, and highly robust solution for next-generation visual data protection.
  • Integrating quantum-inspired optimization with perceptual encoding enhances watermark resilience.
  • This approach presents a promising direction for future research in quantum-secure multimedia systems.