They are looking at how you walk, swipe and hold your device among other methods to not use passwords.
Continuous multi-factor authentication (CMFA) will run seamlessly in the background allowing access through biometric data distinct to each user.
Two years into the program and after 18 months of research, the handsets are now at the Minimally Viable Product stage where they are beginning to meet some user requirements and are garnering feedback for future iterations. Once proven, the authentication capabilities are expected to be used for personal mobile devices, government furnished equipment for both unclassified and classified communications, Wi-Fi kits, tablets, and laptops and/or desktop computers.
There are two primary steps to the program for assured identity on mobile networks.
1. is hardware attestation, where the device itself generates a key to authenticate its hardware and systems.
2. CMFA that relies on sensor data tied to both biometric factors (fingerprint, facial features, retina, and voice) and contextual factors (connections to Bluetooth devices, Wi-Fi networks, and peripherals like monitors). Machine learning algorithms analyze the mix of behavioral and contextual biometric factors to provide continuous authentication in mobile, desktop, and server environment.
Each additional factor can raise a user’s trust score, allowing them to access systems and data as per their network privileges and for longer periods of time.