Novel explanatory hybrid model for classifying deepfake images

Abstract

The proliferation of deepfake images poses significant challenges to digital media authenticity and security. This research article presents a novel explanatory hybrid model for classifying deepfake images. The proposed model combines deep learning techniques with traditional image analysis methods to enhance detection accuracy and provide interpretable results. Through comprehensive experiments, the hybrid model demonstrates superior performance in identifying deepfakes, contributing to the robustness and reliability of digital content verification systems.