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Related Experiment Videos

A new secure approach for AI-based compression across various domains.

Safa S Abdul-Jabbar1, Samira Naji Kadhim2, Amal H Alharbi3

  • 1Computer Science Department, College of Science for Women, University of Baghdad, Baghdad, Iraq. Safa.s@csw.uobaghdad.edu.iq.

Scientific Reports
|May 2, 2026
PubMed
Summary

Related Concept Videos

Distribution Reliability and Automation01:25

Distribution Reliability and Automation

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Distribution reliability in electrical power systems is critical for ensuring an uninterrupted power supply to consumers at minimal cost. According to IEEE Standard Terms, reliability is the probability that a device will function without failure over a specified time period or amount of usage. For electric power distribution, this translates to maintaining continuous power supply and addressing customer concerns over power outages. Several indices, as defined by IEEE Standard 1366-2012, are...
678

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This summary is machine-generated.

This study introduces an integrated system combining data compression and security for financial documents. The Autoencoder and ZSTD approach significantly improves storage efficiency and data security for sensitive information.

Area of Science:

  • Information Security
  • Data Compression
  • Computer Science

Background:

  • Data security is crucial for financial systems, necessitating efficient storage solutions.
  • Existing methods often require a balance between security and storage space.
  • Protecting sensitive financial data while minimizing storage is a key challenge.

Purpose of the Study:

  • To design an integrated system for securing financial data and optimizing storage.
  • To develop a method that classifies data as sensitive or non-sensitive.
  • To evaluate the effectiveness of combining watermarking, encryption, and compression.

Main Methods:

  • Developed a system with sender, receiver, and GUI components.
  • Input documents (images, PDF) were processed, data extracted, and classified.
Keywords:
Chi-square testData compressionFinancial data compressionLossless compressionPrivacy-preservation

Related Experiment Videos

  • Sensitive data was secured using watermarking and encryption, followed by compression.
  • Compared Zstd, LZMA, and Brotli algorithms, selecting the optimal one.

    • Main Results:

    • The proposed Autoencoder and ZSTD system achieved 26.4%–52.8% compression efficiency improvement over traditional ZSTD.
    • High entropy values (5.83–5.99 bits/byte) were maintained, indicating strong security.
    • Chi-square tests yielded high values (up to 11,015), confirming data randomness and security.

    Conclusions:

    • The integrated system effectively enhances financial data security and storage efficiency.
    • The Autoencoder and ZSTD approach offers a robust solution for sensitive data protection.
    • The method ensures data privacy, integrity, and statistical randomness.