Deepfakes Can Effectively Fool Many Major Facial 'Liveness' APIs

A new research collaboration between the US and China has probed the susceptibility to deepfakes of some of the biggest face-based authentication systems in the world, and found that most of them are vulnerable to developing and emerging forms of deepfake attack. The research conducted deepfake-based intrusions using a custom framework deployed against Facial Liveness Verification (FLV) systems that are commonly supplied by major vendors, and sold as a service to downstream clients such as airlines and insurance companies. Facial Liveness is intended to repel the use of techniques such as adversarial image attacks, the use of masks and pre-recorded video, so-called'master faces', and other forms of visual ID cloning. The study concludes that the limited number of deepfake-detection modules deployed in these systems, many of which serve millions of customers, are far from infallible, and may have been configured on deepfake techniques that are now outmoded, or may be too architecture-specific. '[Different] deepfake methods also show variations across different vendors…Without access to the technical details of the target FLV vendors, we speculate that such variations are attributed to the defense measures deployed by different vendors.