Criminal Aspects of Identifying Deepfakes

The contemporary criminal landscape in the Russian Federation is undergoing a paradigm shift driven by evolving operational methods. It demonstrates a significant surge in offenses that utilize artificial intelligence and AI-generated synthetic media (deepfakes). Conducting effective investigations into these crimes requires a precise comprehension of the markers and detection methodologies necessary to establish robust evidentiary verification in court. Based on a comprehensive review of scientific literature and expert reports, these forensic markers can be categorized by source into image, audio, and video data. Their identification involves an intersection of specialized forensic disciplines, including computer, phonographic, phototechnical, portrait, and video-technical examinations. Detecting signs of manipulation relies on identifying the dynamic features of a subject’s altered physical appearance alongside idiolect anomalies within communications, which can be verified through forensic identification examinations. An integrated approach and a multidisciplinary, complex forensic examination are required given the multi-layered complexity of synthetic AI-generated falsifications.

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Publication Details

Journal
Bulletin of Kemerovo State University Series Humanities and Social Sciences
Published
2026-06-30
DOI
https://doi.org/10.21603/2542-1840-2026-10-2-376-383
Primary Topic
Digital Media Forensic Detection
Type
article
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article

Criminal Aspects of Identifying Deepfakes

Yurii Volgin
Bulletin of Kemerovo State University Series Humanities and Social Sciences
Digital Media Forensic Detection
article

Criminal Aspects of Identifying Deepfakes

Yurii Volgin
article en

Abstract

The contemporary criminal landscape in the Russian Federation is undergoing a paradigm shift driven by evolving operational methods. It demonstrates a significant surge in offenses that utilize artificial intelligence and AI-generated synthetic media (deepfakes). Conducting effective investigations into these crimes requires a precise comprehension of the markers and detection methodologies necessary to establish robust evidentiary verification in court. Based on a comprehensive review of scientific literature and expert reports, these forensic markers can be categorized by source into image, audio, and video data. Their identification involves an intersection of specialized forensic disciplines, including computer, phonographic, phototechnical, portrait, and video-technical examinations. Detecting signs of manipulation relies on identifying the dynamic features of a subject’s altered physical appearance alongside idiolect anomalies within communications, which can be verified through forensic identification examinations. An integrated approach and a multidisciplinary, complex forensic examination are required given the multi-layered complexity of synthetic AI-generated falsifications.

Bulletin of Kemerovo State University Series Humanities and Social SciencesVol. 10(2)
Kemerovo State University (RU)
Peace, Justice and strong institutions
Openalex Percentile: Top 8%
Digital Media Forensic Detection
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