Analysing the Identification Approaches of Deep Fake Images and Videos Encapsulated in Fake Contents Available on Social Platforms

The 21<sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">st</sup> century is characterized by the emergence of AI tools, which have become essential in today's diverse application landscape. These tools find utility across various sectors such as research, customer service, medical sciences, education, software industries, and factories. AI has the capability to generate images and videos that closely resemble reality, often making it challenging to distinguish between authentic and altered content. In contemporary usage, artificial intelligence software is frequently employed in creating WhatsApp videos and Instagram reels, blurring the line between reality and fabrication. Consequently, there is a tendency for such manipulated content to circulate unchecked, masquerading as genuine news. In this research paper, we aim to examine instances of ostensibly authentic news that have been tampered with using image editing tools. Accurate identification of such manipulated content is crucial, particularly as it may serve as essential legal evidence.