Litcius/Paper detail

Deepfake detection in digital media forensics

Vurimi Veera Venkata Naga Sai Vamsi, Sukanya S. Shet, Sodum Sai Mohan Reddy, Sharon S. Rose, Sona R. Shetty, Singam Sathvika, M. S. Supriya, Sahana P. Shankar

2022Global Transitions Proceedings64 citationsDOIOpen Access PDF

Abstract

With the development of technology and ease of creation of fake content, the manipulation of media is carried out on a large scale in recent times. The rise of AI altered videos or Deepfake media has posed a great threat to media integrity and is being produced and spread widely across social media platforms, the detection of which is seen to be a major challenge. In this paper, an approach for Deepfake detection has been provided. ResNext, a Convolutional Neural Network (CNN) algorithm and Long Short-Term Memory (LSTM) is used as an approach to detect the Deepfake videos. The approach and its steps are discussed in this paper. The accuracy obtained for the developed Deep-Learning (DL) model over the Celeb-Df dataset is 91%.

Topics & Concepts

Computer scienceConvolutional neural networkSocial mediaData scienceArtificial intelligenceDigital forensicsDeep learningMachine learningComputer securityWorld Wide WebDigital Media Forensic DetectionGenerative Adversarial Networks and Image SynthesisAdvanced Steganography and Watermarking Techniques