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Securing Camera and Photography Systems From Deepfakes by Verifying Provenance and Reducing Attack Surfaces (Case No. 2024-270)

Summary: Researchers in the UCLA Department of Electrical and Computer Engineering have developed a multi-layer security framework to verify deepfake imagery data. Background: The exponential improvements in generative AI pose serious implication to the rise of synthetic media or “deepfakes”. Soon, deepfake images and videos will be...

Published: 9/27/2024 | Inventor(s): Alexander Vilesov, Achuta Kadambi, Yuan Tian, Nader Sehatbakhsh

Keywords(s): AI image security, Artificial Intelligence, artificial intelligence algorithms, Artificial Neural Network, Artificial Neural Network Artificial Neuron, artificial-intelligent materials, attack surface reduction, data security, Deep Learning, Deep learning-based sensing, deep physical neural network, deepfake, deepfake protection, deep-learning analysis algorithms, deep-learning fake (deepfake), generative artificial intelligence, image authenticity verification, image provenance, image signal processing, Medical artificial intelligence (AI), social media, third-party verification

Category(s): Software & Algorithms, Software & Algorithms > Artificial Intelligence & Machine Learning, Software & Algorithms > Image Processing, Software & Algorithms > Security & Privacy, Electrical, Electrical > Visual Computing, Electrical > Visual Computing > Video Processing