A Deep Learning Based Deepfake AI (Images & Videos) Detection Tool

Authors

  • Mani Chourasiya Dept. of AIDS, Prestige Institute of Engineering Management and Research, Indore, India
  • Chetan Khapedia Dept. of AIDS, Prestige Institute of Engineering Management and Research, Indore, India
  • Diksha Bharawa Prestige Institute of Engineering Management Research, India

Keywords:

Deep Neural Networks, Convolutional Neural Networks (CNNs), Recurrent Neural Networks (RNNs)

Abstract

Lenscan.ai represents a pivotal advancement in countering the rising threat posed by deepfake technology. This state-of-the-art AI tool integrates sophisticated computer vision and audio analysis algorithms to detect anomalies that signal deepfake manipulation in digital media. By scrutinizing visual indicators such as facial expressions and lip movements, coupled with auditory features like voice characteristics, Lenscan.ai employs a comprehensive, multi-modal approach to accurately identify falsified content. Its versatility extends across diverse media formats and platforms, playing a crucial role in mitigating risks across journalism, entertainment, and national security sectors. As deepfake methods become increasingly sophisticated, Lenscan.ai continues to evolve, ensuring it remains at the forefront of safeguarding the integrity and reliability of digital content. By doing so, it addresses the urgent need to combat misinformation, thereby preserving trust in the digital landscape and upholding the authenticity of information shared globally.

 

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Published

2024-08-31

How to Cite

[1]
M. Chourasiya, C. Khapedia, and D. Bharawa, “A Deep Learning Based Deepfake AI (Images & Videos) Detection Tool”, Int. J. Sci. Res. Net. Sec. Comm., vol. 12, no. 4, pp. 13–20, Aug. 2024.

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Section

Research Article