Though it might seem like an odd question, you want to have a clear and definitive answer for it. Another downstream problem with deepfakes is the lack of trust. Business is built on trust, and how can you trust someone you don’t know to be real?
We have at least an answer or a way to answer someone should they ever ask.
By using Reality Anchor , you will have proof that you are a real person. This has a value is hard to understand until it’s gone
What would you do If you where accused of being a deepfake?
Though it might seem like an odd question, it’s one you want to have a clear and definitive answer for. Another downstream problem with deepfakes is the lack of trust. Business is built on trust, and how can you trust someone who you don’t even know to be real?
We have at least an answer or a way to answer someone should they ever ask.
By working with us, you will be able to show your coworkers that you are a real person. Something that has value is hard to understand until it’s gone
Examples of deepfake Fraude
Deepfake fraud is a real and growing problem. In multiple instances, individuals have used deepfakes to steal anywhere from thousands to millions of dollars. These incidents have been publicly reported numerous times and have occurred more frequently than you think.
Financial institutions must safeguard against this type of fraud. Reality Anchor offers an additional layer of security.
Furthermore, it’s possible for individuals to falsely claim to be victims of deepfakes, even when they were actually involved in legitimate conversations. Our product can also assist in preventing such false claims. While this may not be a current concern, it’s always better to be prepared than unprepared.
Financial institutions must safeguard against this type of fraud. Reality Anchor offers an additional layer of security that can assist you in this endeavour.
How Can You Protect from Fraud and build trust
Various approaches are taken to combating deepfakes, and many people propose using deepfake detectors, which certainly serve a valuable purpose.
However, because deepfakes are constructed using adversarial neural networks, as deepfake detectors improve, deepfakes themselves also become more sophisticated. We believe that eventually, deepfakes may outpace detectors in effectiveness.
Instead, we advocate for a proactive approach that focuses on directly addressing the image itself, thereby presenting the computer with an extremely challenging problem to solve. We primarily employ techniques involving moving lenses, which can significantly enhance the detection of deepfakes. When combined with encryption protocols, this approach can make it exceptionally difficult to commit deepfake fraud, provided that the protocols are followed.
Below you see examples of our product: the handheld version as well as the headset and screen. The screen being the lowest and the headset being the highest level of security. Along with a graphic going over how the technology works.