DEEPFAKE DILEMMA: A REVIEW STUDY ON VIDEO SYNTHESIS TECHNOLOGY - Kedawat, Akshat; Das, Aloke (ShodhKosh: Journal of Visual and Performing Arts, 2024)
This review paper provides information of deepfake video technology, a rapidly evolving dimension of artificial intelligence with profound implication for media, privacy & Society. Exploring the fundamental methods used to create deepfakes, this paper explores the advancements in machine leaning, particularly focusing on Generative Adversarial Networks (GAN)s & Neural Architecture Network responsible for hyper-realistic synthesis of facial expression, gestures and voices. An important part of the investigation is devoted to ethical questions, asking whether deepfake technology might be used as a weapon to spread misinformation, steal identities, or invade privacy. The impact on Society as a whole is highlighted in the report, along with the necessity for preventative actions to lessons the negative consequences of malicious deepfake distribution & the decline in public confidence in digital media The review addresses the persistent challenges of detecting deepfake content, closely examine methodologies from traditional forensics to innovate machine leaning based approaches Highlighting the Cat & mouse game between creators & Detectors, the paper discusses the limitations of existing detection methods & the urgent requirements for more advanced & expandable solution.