Digital identities are becoming more prevalent as organizations increasingly provide remote access to high-value services that had traditionally only been offered in person. As a result of increasing the number of online services, the attack surface for these organizations has grown significantly, and with the online availability of high-value services, so have the potential rewards for bad actors.
To help fortify their defenses, many organizations are quickly adopting biometric face verification as a highly secure and easy-to-use identity assurance method to onboard and re-authenticate users.
Bad actors are also taking advantage of innovative technology however, and are increasingly using generative AI to develop evermore sophisticated ways to commit fraud, launder money, or commit other illicit activities for financial gain. Unfortunately, while most biometric solutions have developed resilience to presentation attacks, many are struggling to defend against the much easier-to-create and more scalable digital injection attacks like deepfakes, face swaps, and even synthetic identities.
To help organizations better understand the anatomy of a biometric attack, iProov is sharing insights gained from our Security Operations Center (iSOC). iSOC utilizes state-of-the-art machine-learning computer vision systems in conjunction with complementary, multimodal approaches to detect biometric attack patterns across multiple geographies, devices, and platforms.
Understanding and uncovering the anatomy of a biometric attack is essential when selecting which biometric solutions are best suited for your organization’s needs.
Read on to learn more about the biometric threat landscape, discover the behavioral trends of threat actors, and understand why all biometric technologies are not created equal when facing these threats.
Using research from our Security Operations Center, the iProov Threat Intelligence Report illuminates the key biometric threats of 2022.