METHODS FOR DETECTING UNAUTHORIZED MODIFICATION OF MULTIMEDIA DATA IN ENSURING INFORMATION SECURITY, USING THE EXAMPLE OF FOURIER TRANSFORM

Abstract: This article reviews existing tools for detecting unauthorized modification of multimedia data and their problems. The article analyzes Fourier transform and statistical models as one of the most widely used methods for detecting manipulation in multimedia documents. The process of determining the frequency spectrum of data and its changes using Fourier transform, as well as analyzing images and videos using statistical methods, is shown. The article also provides an analysis of the main problems encountered in analyzing multimedia data, including the large volume of data and tools for improving the efficiency of analysis. Innovative approaches and methods are considered to ensure the efficiency of analysis, which will allow developing more effective and faster methods for detecting unauthorized modification of multimedia materials.

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Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2025-05-15
DOI
https://doi.org/10.5281/zenodo.15423580
Primary Topic
Digital Media Forensic Detection
Type
article
Field-Weighted Citation Impact
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article

METHODS FOR DETECTING UNAUTHORIZED MODIFICATION OF MULTIMEDIA DATA IN ENSURING INFORMATION SECURITY, USING THE EXAMPLE OF FOURIER TRANSFORM

Zenodo (CERN European Organization for Nuclear Research)
Digital Media Forensic Detection
article

METHODS FOR DETECTING UNAUTHORIZED MODIFICATION OF MULTIMEDIA DATA IN ENSURING INFORMATION SECURITY, USING THE EXAMPLE OF FOURIER TRANSFORM

article en

Abstract

Abstract: This article reviews existing tools for detecting unauthorized modification of multimedia data and their problems. The article analyzes Fourier transform and statistical models as one of the most widely used methods for detecting manipulation in multimedia documents. The process of determining the frequency spectrum of data and its changes using Fourier transform, as well as analyzing images and videos using statistical methods, is shown. The article also provides an analysis of the main problems encountered in analyzing multimedia data, including the large volume of data and tools for improving the efficiency of analysis. Innovative approaches and methods are considered to ensure the efficiency of analysis, which will allow developing more effective and faster methods for detecting unauthorized modification of multimedia materials.

Zenodo (CERN European Organization for Nuclear Research)
Tashkent University of Information Technology (UZ), Tashkent Islamic University (UZ)
Industry, innovation and infrastructure
Openalex Percentile: Top 56%
Digital Media Forensic Detection
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