• Vedashree Vispute
• Amay Patni
• Ishan Patil
• Vipul Gotiwale
• Vama Shaha

The current phase of media manipulation has been brought about by the development of deep fake technology, which presents serious obstacles to the veracity and authenticity of visual content. In response, the novel framework DeepForense—which is intended for enhanced forensic analysis to identify deep fakes—is presented in this research. Using deep learning techniques, DeepForense examines minute clues and discrepancies that may be signs of altered media. Through rigorous testing, our model achieved an impressive accuracy rate of 87.5 percentage in accurately identifying thesemanipulated videos.

Deepfake detection, video or image manipulation, digital media forensics, CNN, GANs

"DeepForense: Advanced Forensic Analysis for Detecting Deep Fakes", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.11, Issue 5, page no.e496-e504, May-2024, Available :http://www.jetir.org/papers/JETIR2405459.pdf

"DeepForense: Advanced Forensic Analysis for Detecting Deep Fakes", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.11, Issue 5, page no. ppe496-e504, May-2024, Available at : http://www.jetir.org/papers/JETIR2405459.pdf