Journal "Software Engineering"
a journal on theoretical and applied science and technology
ISSN 2220-3397

Issue N8 2026 year

DOI: 10.17587/prin.17.426-434
A Dataset for Assessing the Stability of Fake Video Detection in Video Conferencing
M. D. Krasilnikov1, 2, Postgraduate Student, maksim.krasilnikov@graphics.cs.msu.ru, M. Yu. Nikitin2, Lead Researcher, mikhail.nikitin@tevian.ru, A. S. Konushin1, Cand. Sc. (Phys&Math.), Associate Professor, konushin@airi.net
1 Faculty of Computational Mathematics and Cybernetics, Lomonosov Moscow State University, Moscow, 119991, Russian Federation
2 Tevian, Moscow, 119634, Russian Federation
Corresponding author: Maksim D. Krasilnikov, Postgraduate Student, Lomonosov Moscow State University, Moscow, 119991, Russian Federation, E-mail: maximkras505@gmail.com
Received on February 19, 2026
Accepted on March 16, 2026

The FakeMeet dataset is proposed for evaluating the robustness of face-swapping detection algorithms in video recordings under video-conferencing conditions. FakeMeet recreates typical video-call conditions by modeling distortions caused by resolution changes and by H.264 encoding with different compression levels, and it also includes variation in the background. An experimental comparison of fourteen modern detectors is conducted in a cross-domain evaluation setting on the Celeb-DF and FakeMeet datasets. It is shown that, under conditions characteristic of video conferencing, detection performance noticeably decreases. These findings point to the need for stable approaches that remain reliable under resolution shifts, compression artifacts, and the use of different generation methods. FakeMeet provides a standardized, scenario-specific benchmark to drive advancements in securing digital communication platforms against evolving deepfake threats.

Keywords: fake videos, videoconferencing, video communication, fake detection, dataset, evaluation of methods, low resolution, video compression, compression artifacts, variable quality, fake realism, algorithm stability, security, privacy, digital communications
pp. 426—434
For citation:
Krasilnikov M. D., Nikitin M. Yu., Konushin A. S. A Dataset for Assessing the Stability of Fake Video Detection in Video Conferencing, Programmnaya Ingeneria, 2026, vol. 17, no. 8, pp. 426—434. DOI: 10.17587/prin.17.426-434. (in Russian).
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