Results 71 to 80 of about 11,154 (185)
DeepFakes: a New Threat to Face Recognition? Assessment and Detection
, 2018 It is becoming increasingly easy to automatically replace a face of one person in a video with the face of another person by using a pre-trained generative adversarial network (GAN).
Korshunov, Pavel, Marcel, Sebastien
core
SECURITY AND PRIVACY, Volume 9, Issue 1, January/February 2026.ABSTRACT Unarguably, malware and their variants have metamorphosed into objects of attack and cyber warfare. These issues have directed research focus to modeling infrastructural settings and infection scenarios, analyzing propagation mechanisms, and conducting studies that highlight optimized remedial measures.
Chukwunonso Henry Nwokoye
wiley +1 more source
A Comprehensive Analysis of AI Biases in DeepFake Detection With Massively Annotated Databases
, 2023 In recent years, image and video manipulations with Deepfake have become a severe concern for security and society. Many detection models and datasets have been proposed to detect Deepfake data reliably.
Pedersen, Marius +3 more
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Robustness Analysis of Distributed CNN Model Training in Expression Recognition
IET Biometrics, Volume 2026, Issue 1, 2026.Facial expression recognition is vital in pattern recognition and affective computing. With the advancement of deep learning, its performance has improved, yet challenges remain in nonlaboratory environments due to occlusion, poor lighting, and varying head poses.
Jun Li, Jun Wan
wiley +1 more source
Analyzing Fairness in Deepfake Detection With Massively Annotated Databases [PDF]
In recent years, image and video manipulations with Deepfake have become a severe concern for security and society. Many detection models and datasets have been proposed to detect Deepfake data reliably.
Bylappa Raja, Kiran +2 more
core +1 more source
MLC: Enhanced Deepfake Detection Through Multi‐Level Collaborations
IET Image Processing, Volume 20, Issue 1, January/December 2026.A novel Multi‐Level Collaborations (MLC) strategy to enhance the generalisation performance through simultaneously extracting and integrating three distinct levels of discriminative features during the encoding process. Three complementary forge clues: pixel‐level fine‐grained, region‐level facial layout, and semantic‐level deep clues, are integrated ...
Lihua Wang +4 more
wiley +1 more source
Forensic detection of medical image manipulation using PACS and DICOM artifacts
Journal of Forensic Sciences, Volume 71, Issue 1, Page 371-387, January 2026.Abstract With the digitization of medical information, illegal activities such as medical crimes and insurance fraud through tampering have increased. Medical images are particularly vulnerable due to their nature as soft copies and their transmission over networks.
Sojung Oh +5 more
wiley +1 more source
Applied SciencesThe development of artificial intelligence has inevitably led to the growth of deepfake images, videos, human voices, etc. Deepfake detection is mandatory, especially when used for unethical and illegal purposes.
Cosmina-Mihaela Rosca, Adrian Stancu
doaj +1 more source
A destructive active defense algorithm for deepfake face images [PDF]
PeerJ Computer ScienceThe harm caused by deepfake face images is increasing. To proactively defend against this threat, this paper innovatively proposes a destructive active defense algorithm for deepfake face images (DADFI).
Yang Yang +4 more
doaj +2 more sources
AVA: Inconspicuous Attribute Variation-based Adversarial Attack bypassing DeepFake Detection
, 2023 While DeepFake applications are becoming popular in recent years, their abuses pose a serious privacy threat. Unfortunately, most related detection algorithms to mitigate the abuse issues are inherently vulnerable to adversarial attacks because they are ...
Guo, Shanqing +4 more
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