Scan & Detect Deepfakes

In the age of disinformation and propaganda, deepfakes pose an existential threat for individuals, businesses, and governments. Start taking action against deepfakes with Deepware Scanner.

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.

Problem: Deepfake

Deepfake technology can create hyper-realistic fake videos from any given face picture, and today it would only take less than 10 minutes to create one. Deepfake videos bear potential risks such as targeted reputation attacks, misinformation, and propaganda.

Solution: Deepware

We have developed a deepfake detection technology that can identify when a video is altered to mislead the viewer. In simpler words, we detect deepfakes and allowing everyone to see if a particular video is deepfake or not.

Deepware Products

Deepware Scanner

Deepware Scanner is designed to scan media files to detect purposeful and misleading alterations. It’s an easy and accessible way for everyone to resolve the dilemma regarding the integrity of the suspicious video.

  • Easy, fast and free scanning
  • Accurate, reliable results
  • Available API end-points for integration

Deepware Intelligence

Deepware Intelligence provides you with all available deepfake data in one place that has been detected, classified, and labeled for further use. Plus, you can use Deepware Intelligence features to stay alerted from emerging deepfake threats targeting you or your organization while you can monitor the latest deepfake trends.

  • Feed
  • Hunter
  • Monitor

Threat Analysis & Research

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

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.

Continuing to Fight Mosquitoes in Swamp Opening…

Those who develop deepfake detection models are expected to be faster than those who developed deepfake tools to gain an edge over the algorithm war before it is too late. For this, don’t they deserve some time and positive discrimination? Isn’t it necessary to tidy up the open-source platforms that provide unconditional and unregulated ammunition and speed up those who develop deepfake tools and produce deepfakes with the help of these that are not known by whom?

Can Deepfakes Defense Be Personalized?

It seems to take time to develop a general detection model that will provide 100% security against deepfakes. So, can the personalized biometric video and audio security be a deterrent solution for targets, such that the production of their deepfakes will cause great harm?

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