Phocus

Oz Liveness is a leading facial recognition and authentication software used by private and public organizations across the globe to lower the risk of biometric fraud by preventing deepfake and spoofing attacks with 100% accuracy. The technology has been validated by the industry’s most rigorous testing standard, ISO 30107-3 iBeta level 1 and 2 certifications. It helps organizations validate they are dealing with a real person within seconds, lowering compliance and fraud risks. Oz Liveness features advanced algorithms able to detect many forms of biometric spoofing, including 3D and 2D masks and photos along with photos or videos displayed on a mobile or a laptop screen. On-device Liveness detection and face biometry checks allow to use of a phone as a personal biometric device. No data is sent to the server from the device and stays in the customer's hands. On-device Liveness is perfect in any customer’s use case, improving the reachability and stability of the services .

An open platform integrating state-of-the-art deepfake detection methods. You can upload a video from your computer, note that should upload only one video each time. Deepfakes refer to AI-synthesized fake media, by creating illusions of an individual's presence and activities that did not occur in reality, deepfakes can cause real harm when they are weaponized. DeepFake-o-meter is an open source and user-friendly online platform developed by the UB Media Forensics Lab to detect third-party deepfake algorithms. For users, it provides a convenient service to analyze deepfake media with multiple state-of-the-art detection algorithms, with secure and private delivery of the analysis result. For developers of deepfake detection algorithms, it provides an API architecture to wrap individual algorithms and run them on a remote machine. For researchers of digital media forensics, it is an evaluation/benchmarking platform to compare the performance of multiple algorithms.