The widespread availability of tools to produce and disseminate fake information poses a growing danger to people, businesses, and government agencies worldwide. The Internet allows for the creation of an "alternative" reality where false allegations and subsequent apologies have little to no effect on the situation. A significant amount of digital media information is created and circulated every day; at the moment, the primary facilitators of fake news circulation are social media networks. Quite easily, in this "flood," material may be manipulated to influence its users. This highlights the critical need of working on efficient countermeasures. This study proposes and describes the architecture of a system for detecting fake news, which is currently being developed as part of the Identification of fake news on social media platforms (FNSMP’s) project, in light of the above. Its primary purpose is to secure digital media files, such as movies, TV shows, and music, and it employs several different methods, including digital fake news, signal processing, and machine learning.