AI Article Synopsis

  • SecureVision is a deepfake detection system designed to combat manipulated media, aiming to protect public trust and cybersecurity.
  • It uses a combination of big data analytics and deep learning algorithms with a multi-modal analysis approach, allowing it to detect changes in both audio and visual content effectively.
  • The system is flexible and efficient due to its use of large datasets and self-supervised learning, setting a new standard for privacy and security in response to the rise of digital deception.

Article Abstract

SecureVision is an advanced and trustworthy deepfake detection system created to tackle the growing threat of 'deepfake' movies that tamper with media, undermine public trust, and jeopardize cybersecurity. We present a novel approach that combines big data analytics with state-of-the-art deep learning algorithms to detect altered information in both audio and visual domains. One of SecureVision's primary innovations is the use of multi-modal analysis, which improves detection capabilities by concurrently analyzing many media forms and strengthening resistance against advanced deepfake techniques. The system's efficacy is further enhanced by its capacity to manage large datasets and integrate self-supervised learning, which guarantees its flexibility in the ever-changing field of digital deception. In the end, this study helps to protect digital integrity by providing a proactive, scalable, and efficient defense against the ubiquitous threat of deepfakes, thereby establishing a new benchmark for privacy and security measures in the digital era.

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Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC11478486PMC
http://dx.doi.org/10.3390/s24196300DOI Listing

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