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Hype-busting single pixel change enough to spoof AI image-spotters

Researchers from Japan’s Kyushu University have discovered that they can trick three-quarters of image-recognizing deep neural networks by altering just a single pixel in an image. Using three pixels achieved an 82% success rate, and five netted 87.3%. While difficult to weaponize, the research shows how fragile these systems are – despite what you will have heard through marketing materials. Setting out with two objectives, to predictably fool a Deep Neural Network (DNN) and to automate said attack, the researchers found that an ‘adversarial perturbation’ of a single pixel could trick the DNN – an attack that would be very difficult for a human inspector to spot and address. As the paper’s abstract notes, “the output of DNNs is not…

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