Combating Deepfakes : A Review of Detection Techniques and Their Limitations

Deepfake technology, powered by advanced AI, enables the creation of highly realistic but entirely synthetic audio, video, and image media. While this technology has legitimate applications, it also poses significant security risks. This thesis provides a comprehensive structured literature review and analysis of the risks associated with deepfake technology and critically examines the challenges in currently available detection methods. The study categorizes the main risks into three main categories: Dis- and Misinformation and Manipulation, Identity Theft and Fraud, and Privacy Invasion and Blackmail. It also identifies critical challenges in detection methods including technical limitations and privacy concerns. This thesis contributes to the field by providing a clear understanding of the threat landscape associated with deepfakes, identifying gaps in detection methods, and offering insights for future research.

Publication Details

Journal
KTH Publication Database DiVA (KTH Royal Institute of Technology)
Published
2025-01-01
Primary Topic
Generative Adversarial Networks and Image Synthesis
Type
article
Field-Weighted Citation Impact
0.00
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article

Combating Deepfakes : A Review of Detection Techniques and Their Limitations

KTH Publication Database DiVA (KTH Royal Institute of Technology)
Generative Adversarial Networks and Image Synthesis
article

Combating Deepfakes : A Review of Detection Techniques and Their Limitations

article en

Abstract

Deepfake technology, powered by advanced AI, enables the creation of highly realistic but entirely synthetic audio, video, and image media. While this technology has legitimate applications, it also poses significant security risks. This thesis provides a comprehensive structured literature review and analysis of the risks associated with deepfake technology and critically examines the challenges in currently available detection methods. The study categorizes the main risks into three main categories: Dis- and Misinformation and Manipulation, Identity Theft and Fraud, and Privacy Invasion and Blackmail. It also identifies critical challenges in detection methods including technical limitations and privacy concerns. This thesis contributes to the field by providing a clear understanding of the threat landscape associated with deepfakes, identifying gaps in detection methods, and offering insights for future research.

KTH Publication Database DiVA (KTH Royal Institute of Technology)
Peace, Justice and strong institutions
Openalex Percentile: Top 47%
Generative Adversarial Networks and Image Synthesis
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