Real-Time Deepfake Detection in Online Communication: A Review of AI-Based Audio-Visual Detection Techniques and a Proposed Yii2–MySQL Framework

The advancement of artificial intelligence and generative technologies has increased the realism and accessibility of manipulated audio and video content, creating challenges for multimedia authenticity, digital communication and information security. This study presented a literature-based review of AI techniques for detecting video deepfakes, synthetic speech and multimodal audio-visual manipulation. The review also considered benchmark datasets and evaluation measures, including accuracy, precision, recall, F1-score, AUC and EER, together with processing latency and computational requirements. The study further examined the technical requirements of real-time detection in online communication, including continuous media processing, computational efficiency, network conditions, privacy, security and scalability. Based on these requirements, a conceptual web-based application framework was proposed using the Yii2 PHP framework and MySQL database.

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