Deep fake Detection

• Author(s): K. Rakesh ; M. Veera Mani Kanta ; M. Mahesh Reddy ; M. Tejaggna ; Ms. R. Tejaswini
• Paper ID: 1702830
• Page: 182-187
• Published Date: 10-07-2021
• Published In: Iconic Research And Engineering Journals
• Publisher: IRE Journals
• e-ISSN: 2456-8880
• Volume/Issue: Volume 5 Issue 1 July-2021

Abstract

The expeditious progress in facial image generation and exploitation has now come to a point where it raises serious concerns to the social and political society. This leads to the creation of fake information and new which ultimately results in loss of trust in digital content. We have developed a detection model using convolution neural network (CNN) for face detection and Recurrent neural network (RNN) for video classification. Even though this technology is remarkable it leads to social and political concerns. So far, with the help of released tools for the generation of deep fake videos have been widely used to create fake celebrity videos or revenge porn and fake political speeches, etc. Governmental entities are already looking into the issue of these fake videos which are likely to create political tensions. so, it is essential to have a tool for detecting these fake videos. (We need AI to fight an AI)

Keywords

Convolution Neural Networks (CNN), LSTM, RNN.

Citations

IRE Journals:
K. Rakesh , M. Veera Mani Kanta , M. Mahesh Reddy , M. Tejaggna , Ms. R. Tejaswini "Deep fake Detection" Iconic Research And Engineering Journals Volume 5 Issue 1 2021 Page 182-187

IEEE:
K. Rakesh , M. Veera Mani Kanta , M. Mahesh Reddy , M. Tejaggna , Ms. R. Tejaswini "Deep fake Detection" Iconic Research And Engineering Journals, 5(1)