The threat of image forgery and DeepFake (DF) video has accelerated. Since we began the H2020 application: the concern for and impact of DF in media and social media has exploded.
For the purpose of this report we define DF as Artificial Intelligence (AI) assisted manipulation and/or creation of ex nihilo images/video shifting the burden from humans to the AI. DF is now not only an economic threat, but a growing concern for both national and societal security.
Quantum Integrity (QI) has a significant scientific lead on its competitors, and has anticipated the threat of DF:
further links to press reports can be found at www.quantumintegrity.ch(opens in new window).
Pressing this advantage and using feedback from customers - QI has fine-tuned its forgery detection systems and is developing a DeepLearing (DL) based Generative Adversarial Network (GAN) that includes a forgery creator working in competition with a forgery detector to stay one step ahead of new attack methods and DF. These algorithms can be customer specific detection: tailored to needs and use cases, or more generic detectors destined for B2C use. Furthermore, due to the DL forgery creator, QI’s AI can be trained in hours to detect new forms of attacks, as opposed to the weeks needed with current technologies.
The B2B aspect is aimed at streamlining workflow, and saving time and money to companies receiving digital images : Insurance, KYC, Warranty management, HR are examples. Our tool is tailor made for use cases and verticals to address their specific problems.
A more Generic B2C product will be developed to allow the public to detect and defend against malicious DeepFake images or videos.
The overall objective is to become the leader in the space of image and video forgery detection.
