See how IDVoice for ChatGPT authenticates voicebot users without friction in this demo provided at Voice & AI 2023.
Resource Center
Webinar: Will Deepfakes Deep-Six Biometrics?
Deepfakes have been identified as a looming fraud risk for years, but the introduction of ChatGPT has put a point on the fact that it won’t be long before we are interacting online with machines that are “virtually” indistinguishable from humans. Learn how biometrics and liveness detection have evolved to protect us from deepfake- and chat-powered fraud.
Video: IDLive® Face Plus
See how IDLive Face Plus detects presentation and injection attacks without adding friction for users.
White Paper – Deep Dive into Deepfakes
Mitigating the growing threat to biometric security posed by fake digital imagery and injection attacks
Webinar: Securing Identity in a World Shared with Virtual Humans
Deepfakes have been identified as a looming fraud risk for years, but the introduction of ChatGPT has put a point on the fact that it won’t be long before we are interacting online with machines that are “virtually” indistinguishable from humans. Learn how biometrics and liveness detection have evolved to protect us from deepfake- and chat-powered fraud.
IDLive® Face Plus – Injection Attack Detection
Protect biometric security from deepfakes and other types of fraudulent digital imagery by detecting injection attacks, which pose a vulnerability where hardware and software hacks are used to bypass a proper capture process. Without countermeasures, fraudsters can emulate camera capture with non-live digital facial imagery in a way that can defeat certain liveness detection measures.
White Paper – Human or Machine: AI Proves Best at Spotting Biometric Attacks
One might even assume that people are better at liveness detection than computers. ID R&D conducted a formal experiment to help determine which is better at liveness detection, people or machines?
White Paper – Single-Frame Facial Liveness Detection – How It Works to Reduce User Friction and Abandonment
This paper discusses how single-frame facial liveness detection works and presents a case study of its impact on the
onboarding operations of a retail bank.