Maryland Patent of the Month – March 2021
Deepfakes are synthetic media in which a person in an existing image or video is replaced with someone else’s likeness. The term comes from the combination of “deep learning” and “fake” as they use artificial intelligence and neural networks to create fake content. Deepfakes are incredibly realistic and hard to spot with the human eye. They can be used to make funny videos or for more sinister purposes like blackmail. Previous attempts at developing detection methods are limited and have low success rates. ZeroFOX, Inc has developed a new method to accurately detect deepfakes.
ZeroFOX’s method uses a combination of weak and strong classifiers to determine the authenticity of a video. A strong classifier is a network trained to learn to directly classify. In the case of deepfake, this would involve a single classifier that attempts to classify a video or image as “real” or “fake”. A weak classifier is a neural network trained to analyze and detect certain characteristics. On their own, weak classifiers only loosely predict a true classification. The weak classifier is trained on real videos and known synthetic videos to detect irregularities. They make a prediction and send it to a server. The strong classifier takes these predictions and makes the final call on the video’s authenticity.
About ZeroFOX. Inc.
ZeroFOX is a cyber security company based in Baltimore, Maryland. It provides cloud-based software as a service for organizations to detect risks found on social media and digital channels, such as phishing, malware, scams, impersonator accounts, piracy, counterfeit and more.
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