Automated detection and prevention of deepfake content in digital news reporting
1 Department of ECE, Visvesvaraya Technological University, Belagavi, Karnataka, India.
2 Department of CSE, Kent State University, Kent, Ohio, USA.
Review Article
World Journal of Advanced Research and Reviews, 2022, 14(03), 890-894
Publication history:
Received on 19 May 2022; revised on 25 June 2022; accepted on 29 June 2022
Abstract:
Deepfakes, which are created using sophisticated artificial intelligence and machine learning, present a significant and growing danger to the credibility of authentic news reporting. This review examines the effect of these highly realistic, fabricated images, videos, and audio recordings on the integrity of news. It also investigates current methods for detecting deepfakes and considers various strategies for mitigation to safeguard the authenticity of journalism. The increasing accessibility of deepfake technology facilitates the spread of misinformation, which can erode public trust, influence public opinion, and harm the reputations of individuals and institutions. In response, a variety of detection techniques are being developed, including AI-driven analysis and digital watermarking. A comprehensive approach, combining technological solutions, public education, and strategic policy-making, is essential to address this evolving challenge and uphold the standards of trustworthy reporting.
Keywords:
Deepfakes; News Integrity; Artificial Intelligence; Misinformation; Deepfake Detection; Media Authenticity; Journalism; Disinformation
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Copyright information:
Copyright © 2022 Author(s) retain the copyright of this article. This article is published under the terms of the Creative Commons Attribution Liscense 4.0