Scan & Detect
Deepfake Videos

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Cybersecurity faces an emerging threat generally known as deepfakes. Malicious uses of AI-generated synthetic media, the most powerful cyber-weapon in history, is just around the corner.

Deepware Scanner is designed to detect manipulation in the video representation of people

Deepfakes are realistic AI-generated videos that show real people doing and saying fictional things. Such aggregations are extremely difficult for humans to detect, and we can be easily manipulated to believe that something fake is real. Deepware Scanner resolves a dilemma in the reality of media content. It is designed to analyze media files, scanning for AI-generated media alterations and other types of audio-visual manipulation with malicious intent of financial, social, or political gain.

Threat Analysis & Research

Explore our blog for insightful articles, personal reflections, and ideas about AI-generated synthetic threats.


Deepfakes Can Put Flesh on the Bones of Artificial Consciousness…

It should never be forgotten that in the eternal reality of the heavenly religions, creator of all creatures is one. Here, AI-oriented algorithms and robotic technologies transform this single and unchangeable reality into a more flexible perception with digital illusion. It reveals a person who has passed away fictionally in digital life, at first with his/her voice and gestures. Perhaps as deep learning algorithms improve, fiction will no longer be needed after a while.


Do Deepfakes Reveal the Truth?

We will try to question the newest and ironic legitimacy trial of deepfakes: Do deepfakes, which are produced with the help of artificial intelligence (AI) in digital audio, text, and video formats and is the common name for all lies, fraud, forgery, manipulation, and disinformation in the online world, reveal the hidden truths?

Fiction, fake news, and falseness are the basic building blocks of deepfakes.


Deepfake Reverse Engineering Challenge (DREC)

Facebook’s CTO, Mike Schroepfer, explains that Facebook will keep detection technology secret to avoid reverse engineering. However, Facebook does not show the same sensitivity for the most successful deepfake detection algorithms listed in DFDC. Schroepfer stressed that they will keep their algorithms confidential and admitted that they will offer reverse engineering opportunities by publishing them with open source code for algorithms developed in DFDC.