Deepfakes are no longer just amusing YouTube videos. Fraudsters are beginning to use them for business email compromises. Cyber experts say phone scams, sham celebrity endorsements, biometric fakes and bogus evidence could quickly follow. Now’s the time
to advise your organizations.
The last-minute swing of an election, widespread civil unrest, intercontinental nuclear weapon launches — these are the most sensational of potential outcomes of “deepfakes.” Computer techs and cybercriminals are using artificial intelligence to manipulate
video and audio clips to fabricate reality and prompt visceral responses from target audiences. And now slithery types will increasingly use them to commit fraud.
The first iteration of this technology debuted in a paper published by University of Washington researchers in the summer of 2017. They used machine learning — a subset of artificial intelligence — to combine pre-existing audio and video clips of former
President Barack Obama to create a realistic, lip-synced video. (See Lip-syncing Obama: New tools turn audio clips into realistic video,
by Jennifer Langston, UW News, July 11, 2017.)
The most popular type of technology used to make sophisticated deepfakes is Generative Adversarial Networks (GANs), in which one artificial intelligence program (the generator) uses machine learning to create manipulated media and another (the discriminator)
evaluates that media for authenticity. The two go back and forth until the discriminator evaluates the media created by the generator as authentic. [See A Beginner’s Guide to Generative Adversarial Networks (GANs),
by Chris Nicholson, Skymind.]
The deepfake moniker applied to this phenomenon emerged from origins no less disturbing than the dystopian scenarios the technology evokes. In November 2017, a user on the website Reddit began posting altered pornographic video clips featuring the faces
of female celebrities superimposed over adult film actors from an account with the username “deepfakes.” The rest is history … and pseudohistory.
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