Fujitsu Laboratories Ltd. announced the development of a facial recognition technology that uses conventional cameras to successfully identify efforts to spoof authentication systems. This includes impersonation attempts in which a person presents a printed photograph or an image from the internet to a camera.
Conventional technologies rely on expensive, dedicated devices like near-infrared cameras to identify telltale signs of forgery, or the user is required to move their face from side to side, which remains difficult to duplicate with a forgery. This leads to increased costs, however, and the need for additional user interaction slows the authentication process. To tackle these challenges, Fujitsu has developed a forgery feature extraction technology that detects the subtle differences between an authentic image and a forgery, as well as a forgery judgment technology that accounts for variations in appearance due to the capture environment.
Fujitsu’s new technology ultimately makes it possible to prevent impersonation with forgeries using only face images taken at the time of authentication, enhancing security without sacrificing the convenience of face authentication and contributing to the DX (digital transformation) of operations with improved personal authentication technologies.
Growing Risk of Fraud Using Facial Images with Popularity of Biometric Authentication
While biometric authentication continues to grow in popularity, many risks remain. In some cases, when facial images are disclosed on the Internet via SNS, etc., the possibility emerges that the image may become the target of malicious users if stolen due to the loss of an ID card with a facial photograph, etc.–because of the prevalence of such images, this makes facial authentication more vulnerable than other authentication methods, such as fingerprints or palm veins.
Challenges
Smartphone screens, ID cards, and face images printed on paper vary in their appearance due to factors like reflections or blurring on a smartphone screen. It has proven difficult to determine the authenticity of a face by relying on a facial image alone because of the effects of similar fluctuations, such as reflections caused by fluorescent lights or sunlight, or blurring caused by facial movement. For this reason, special cameras like near-infrared cameras or depth cameras that measure the distance between the subject and the camera are used to catch typical signs of forgery. These methods remain imperfect, however, and lead to issues including increased costs for dedicated cameras and reduced convenience due to the addition of motion information required when using general-purpose cameras. The development of technologies that can conveniently and inexpensively detect spoofing with general-purpose cameras has become a topic of consideration.
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