Trust no more: The rise of deceitful deepfake technology. #Deepfakes

In 2017, the emergence of deepfakes, created using a sophisticated deep-learning algorithm, caused shockwaves by superimposing celebrities’ faces onto adult film actors’ bodies. This technology has the potential to cause severe harm and threaten societal security. Traditional approaches to detect deepfakes focus on pixel distribution inconsistencies, but the evolution of deep-learning technology has made these methods vulnerable. Generative Adversarial Networks (GANs) are a leading technique in deepfake generation, allowing for the creation of increasingly realistic images over time. New deepfake detection methods are now focusing on deep-learning approaches, using convolutional neural networks for feature extraction. Researchers are working on developing detection models that specifically target deepfake images from diverse sources to enhance effectiveness in real-world scenarios. Continuous adaptation and innovation are necessary to combat evolving deepfake techniques and ensure responsible use. The development of deepfake detection technology is crucial in preserving authenticity and truth in an era where deepfakes blur the line between reality and fiction. It serves as a beacon in the pursuit of accuracy and truth, ensuring that even in the age of deepfakes, seeing can still mean believing.

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Source link: https://lens.monash.edu/@technology/2024/05/02/1386619/deepfakes-when-you-cant-trust-your-eyes-anymore