A Comprehensive Analysis on Web-Based Deep Fake Detection Techniques
R Shyama, Anakh Krishna T A, Akshaya Jayaraj, Aswin Snil, Chinnu Maria Varghese, H Lakshman · 2024
Deepfake technology has emerged as a critical challenge to the authenticity of digital media, necessitating effective detection techniques. This review explores various advancements in deepfake detection tools, with a particular focus on web-based solutions designed to enhance user capabilities in detecting manipulated images. This study evaluates the effectiveness of these tools, which utilize advanced machine learning algorithms to analyze visual cues and identify inconsistencies that indicate deepfake manipulation. This review highlights the integration of user-friendly interfaces and robust detection mechanisms that address the spread of misinformation. Additionally, this study examines the role of diverse training datasets in improving the detection accuracy and the tool's importance on transparency and user education to enable digital literacy. This review aims to provide an overview of the current approaches and methodologies in deepfake detection, contributing to the effort of preserving digital content integrity and trustworthiness.