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Related Experiment Video

Updated: Jan 8, 2026

A New Technique for Quantitative Analysis of Hair Loss in Mice Using Grayscale Analysis
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A New Technique for Quantitative Analysis of Hair Loss in Mice Using Grayscale Analysis

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A custom hash algorithm for hosting secure gray scale image repository in public cloud.

Veenasri Murugesan1, Nithya Chidambaram2, Rengarajan Amirtharajan1

  • 1School of Electrical & Electronics Engineering, SASTRA Deemed University, Thanjavur, 613401, India.

Scientific Reports
|December 13, 2025
PubMed
Summary
This summary is machine-generated.

This study introduces a novel block-based hash algorithm for secure cloud image storage, enhancing data integrity and tamper detection. The system effectively identifies modified image regions, ensuring reliable data security in cloud environments.

Keywords:
Cloud storageData integrity verificationImage hashingTamper detection

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Area of Science:

  • Computer Science
  • Information Security
  • Cloud Computing

Background:

  • Data breaches during storage and transmission pose significant challenges in digital technology.
  • Traditional data loss prevention (DLP) methods struggle with massive data volumes.
  • Cloud computing offers a scalable and robust solution for data security and management.

Purpose of the Study:

  • To propose a custom block-based hash algorithm for generating digital fingerprints of grayscale images.
  • To enhance data integrity, enable tamper detection, and accurately identify tampered regions in images stored in the cloud.
  • To incorporate user-level authentication and develop a GUI for practical application.

Main Methods:

  • Developed a custom block-based hash algorithm for generating image hash values.
  • Implemented a cloud environment for secure storage and management of digital fingerprints.
  • Integrated user-level authentication and created a Graphical User Interface (GUI) for hash generation and tamper verification.

Main Results:

  • The proposed algorithm successfully generates digital fingerprints for tamper-proofing entire images (256x256).
  • Integrity validation is achieved by comparing generated digests with original ones.
  • The algorithm demonstrated good performance in quantitative and qualitative tests for integrity codes, collision property, and avalanche effect.

Conclusions:

  • The custom block-based hash algorithm effectively ensures image data integrity and tamper detection in cloud storage.
  • The developed framework, including GUI and user authentication, provides a secure and user-friendly solution for managing image security.
  • The proposed method offers a scalable and reliable approach to combatting data breaches in cloud environments.