Deepfake technology has rapidly evolved, enabling the creation of highly convincing synthetic media, including images, videos, and audio recordings. These maliciously manipulated digital artifacts can have severe consequences for privacy, security, and trust in digital content. Therefore, the development of effective deepfake detection methods is of paramount importance. This paper proposes a novel approach for deepfake detection based on the analysis of human eye blinking patterns. The human eye blink is a unique and subtle behavioral trait that is challenging to replicate accurately in deepfake videos. We leverage this inherent biometric feature to identify anomalies in video content and distinguish between genuine and synthetic videos.
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Miss. Namita Survase (2024) studied this question.
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