Advanced framework for multilevel detection of digital video forgeries.

The rapid expansion of digital media has sparked significant concerns regarding the swift dissemination and potential misuse of forged video content. Existing forgery detection technologies primarily focus on simple forgeries and are still evolving, resulting in a critical gap in the detection of multilevel forgeries, where one forgery is layered over another. This paper presents an innovative framework designed to address this challenge by extracting intricate features from forged frames using attention-augmented convolutional neural networks (AACNNs).