A Comprehensive Review of Deepfake Generation, Detection, and Societal Implications

Deepfakes have emerged as one of the most influential applications of deep learning in multimedia generation and manipulation. Using advanced generative models, realistic synthetic images, videos, and voices can now be produced with minimal effort. While this technology offers innovative applications in entertainment, education, and human–computer interaction, it also introduces serious risks including misinformation, identity fraud, and erosion of public trust in digital media. This paper presents a comprehensive review of deepfake technologies, including their technical foundations, major generation approaches, types of manipulations, and current detection strategies. In addition, the paper discusses ethical, legal, and social implications as well as emerging countermeasures such as media provenance frameworks and watermarking techniques. Finally, open research challenges and future directions are outlined to support the development of trustworthy multimedia ecosystems.

کلیدواژه ها:

Deepfake ، Deep Learning ، GAN ، Media Forensics ، Deepfake Detection ، Synthetic Media ، AI Ethics