DeepFake Detection: Detecting A Real and Fake Images Approach Using Machine Learning

Deep learning has revolutionized various fields including computer vision, big data analytics, and automation.However, the same technologies that drive innovation have also enabled the rise of deepfakes-AIgenerated media designed to mimic real human expressions and voices with alarming accuracy.This paper presents a comprehensive overview of the mechanisms behind deepfake creation and critically evaluates the current state of detection techniques.Through a review of literature and research methodologies, we examine the evolution of both generation and detection approaches, discuss emerging challenges, and propose future directions for enhancing the robustness of deepfake detection systems.This work aims to provide a solid foundation for researchers and developers striving to mitigate the misuse of deepfake technology and preserve digital integrity.sequences in videos, and inconsistencies in spatial features.

Publication Details

Journal
IJARCCE
Published
2025-05-20
DOI
https://doi.org/10.17148/ijarcce.2025.14597
Primary Topic
Digital Media Forensic Detection
Type
article
Field-Weighted Citation Impact
0.00
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article

DeepFake Detection: Detecting A Real and Fake Images Approach Using Machine Learning

IJARCCE
Digital Media Forensic Detection
article

DeepFake Detection: Detecting A Real and Fake Images Approach Using Machine Learning

article en

Abstract

Deep learning has revolutionized various fields including computer vision, big data analytics, and automation.However, the same technologies that drive innovation have also enabled the rise of deepfakes-AIgenerated media designed to mimic real human expressions and voices with alarming accuracy.This paper presents a comprehensive overview of the mechanisms behind deepfake creation and critically evaluates the current state of detection techniques.Through a review of literature and research methodologies, we examine the evolution of both generation and detection approaches, discuss emerging challenges, and propose future directions for enhancing the robustness of deepfake detection systems.This work aims to provide a solid foundation for researchers and developers striving to mitigate the misuse of deepfake technology and preserve digital integrity.sequences in videos, and inconsistencies in spatial features.

IJARCCEVol. 14(5)
Openalex Percentile: Top 90%
Digital Media Forensic Detection
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