Year: 2025
Type: article
Abstract: : In the past few years there is vast increase in the technology and the usage of modern technologies which incorporate artificial intelligence were reaching its peak among the peoples. As the technology advances, the possibilities of involving digital crimes were one of the considerable issues and needed to mitigate in various method. One of the issue that related to it was deepfakes (DFs) which involves in morphing the faces, shape, background, voices, vocal lines, sounds and texts. This paper presents the project “DeepScan Sentinel: Multimodal Deepfake Detection & Cybersecurity Platform” to identify the deepfake in the digital media like images, videos, audios and texts in a single platform by integrating the artificial intelligence and machine learning for its identification. It also consists of various other cybersecurity tools to practice and using in real time usage which helps to learning cybersecurity for beginners. By using this platform we can quickly and effectively identify the morphed part of the digital data. In other platforms there is no combined method of identification to identify the deepfakes in digital media. But this platform had image, videos, audio and texts morphing identification methods together in one screen, which will help the users in more efficient way to identify the deepfakes in digital media. And apart from that it had some awareness contents, that could help the users to get some knowledge about the deepfakes, how it was created and further how we can identify that.
Author: KamalaKannan R
Language: English
Subfield: Computer Vision and Pattern Recognition
Field: Computer Science
Domain: Physical Sciences
Open Access status: diamond
OpenAlex ID: W4410118458