For instance, in the state of California, two bills passed last year made aspects of Deepfake illegal - AB-602 banned the use of human image synthesis to make pornography without the consent of the people depicted and AB-730 banned manipulation of images of political candidates within 60 days of an election.īut is this going far enough? Fortunately, cyber-security companies are coming up with more and better detection algorithms all the time. Legislation is already beginning to address the threats of Deepfake videos. How can we protect ourselves against Deepfake? As the technology becomes cheaper, expect to see more uses of Deepfake to blackmail and defraud. Or intruders could get into your network simply by synthesizing a video call from your Chief Information Officer, tricking employees into giving up passwords and privileges, which then lets hackers run riot all over your sensitive databases.ĭeepfake porn videos have already been used to blackmail female reporters and journalists, such as Rana Ayyub in India, who exposes abuses of power. It's also possible that Deepfake authors could blackmail company presidents by threatening to publish a damaging Deepfake video unless they're paid off. Fraudster Gilbert Chikli is alleged to have disguised himself as the minister to ask wealthy individuals and company executives for ransom money to liberate French hostages in Syria he's currently standing trial. In France, a recent fraud didn't use Deepfake tech, but used impersonation, together with meticulous copying of Foreign Minister Jean-Yves le Drian's office and its furnishings, to defraud senior executives of millions of euros. This time, alarm bells rang - but it was too late to get back the funds he'd already transferred. The CEO only became suspicious when his 'boss' requested another transfer. The fake was so convincing that he didn't think to check the funds were wired not to the head office, but to a third party's bank account. The CEO of a British energy firm was tricked out of $243,000 by a voice Deepfake of the head of his parent company requesting an emergency transfer of funds. But increasingly they're being used in major attempts at blackmail and fraud.
Deepfake threats - fraud and blackmailĭeepfake videos have been used for political purposes, as well as for personal revenge. And many celebrity women have found themselves 'starring' in revenge porn made by morphing their faces into porn films and images. A video of Nancy Pelosi 'drunk' scored millions of views on YouTube – but it was simply a fake made by slowing down a video artificially to give the effect of her slurring her words. However, the voice impersonation wasn't as good as Jordan Peele's Obama and gave the truth away.īut even less well-made fakes can have a remarkable impact. The original video comes from a speech he gave on Russian election interference - just 21 seconds of that speech were enough to synthesize the new video.
His advice? We need to question what we see.Ī video of Facebook CEO Mark Zuckerberg appearing to talk about how Facebook ’controls the future’ via stolen user data - notably on Instagram. He then showed how the two halves of the merged video looked when separated. One example of a Deepfake is the video issued by actor Jordan Peele in which he used real footage of Barack Obama merged with his own impression of Obama to issue a warning against Deepfake videos. High profile Deepfake examples are not hard to find.
In fact, the same Deepfake machine learning and synthesizing techniques can be used to fake voices. Plus, GANs can fake other data besides photos and video. This makes Deepfake an ever more potent threat. Two neural networks are used to compete with each other in learning the characteristics of a training set (for instance, photographs of faces) and then generating new data with the same characteristics (new 'photographs').īecause such a network keeps testing the images it creates against the training set, the fake images become increasingly convincing. This is another kind of specialized machine learning system. That data can then be processed in order to create a Deepfake video through a GAN (Generative Adversarial Network). For instance, an AI can gather data on your physical movements. It's capable of learning from unstructured data - such as the human face. Deep learning is an advanced Artificial Intelligence (AI) method which uses multiple layers of machine learning algorithms to extract progressively higher-level features from raw input. Deepfake videos are a portmanteau word - 'deep' from 'deep learning' and 'fake', obviously, from 'fake'.
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