Ethical and Legal Concerns of Deepfake Technology in Biomedical Imaging: A Comprehensive Survey

Deepfakes have posed severe challenges to healthcare systems as fake medical images and videos can be utilized to disseminate fake information about an organization or person. The challenges have open room for more solutions to address them. Therefore, this study provides a survey that highlights the considerable strides made in the development of deepfake detection technologies while showcasing various approaches, from advanced machine learning techniques to multi-modal systems. The progress made in identifying deepfakes, particularly with regard to deep learning and hybrid models, shows promise for detecting alterations in digital content and medical imaging. But the use of these technologies shows differing degrees of efficacy, suggesting the necessity for customized detection tactics that take into account the particular difficulties of certain domains, such as nuclear medicine and endoscopic videography. In addition, the application of these technologies raises significant ethical and legal questions, such as those pertaining to data security, privacy, and possible abuses of artificial intelligence. Therefore, it becomes critical to provide a survey on these issues in order to build and apply deepfake detection tools responsibly.