An Analytical Perspective on Various Deep Learning Techniques forDeep Fake Detection
Usha Kosarkar, Gopal Sakarkar, Shilpa Gedam
Abstract
The advent of deep fake technology has become a crucial concern in this digital world. A serious threat to an individual's privacy, democracy, and national security can be caused by deep fake. Deep fake algorithms can develop forgery multimedia content that we cannot distinguish from genuine ones. In this era of the cyber age, it has become seemingly difficult to identify between real digital content and fake content which are published across the Internet. It is a widely used technology used by cybercriminals to deceive security systems. If we are not cautious, deep fake technology can bring about a serious threat to the future of identity verification. There are many open-source and free software available to create deep fake content which makes it easy for amateurs to create technically brilliant digital content which is fake. On the other hand, many structured and efficient technologies have been developed to identify deep fakes. A few of the techniques available are like comparing the background, analyzing the pattern in the image, considering the blinking of the Eye, considering facial attributes, considering the head position, etc. This paper gives an introduction to deep fake, and a brief on deep fake creation and detection techniques..