Veridium announced the availability of its new behavioral biometric, Veridium InMotion for VeridiumID, a software-only platform for mobile biometric authentication. Veridium InMotion utilizes user behavior analytics (UBA) to better protect users' identities and prevent malicious activity before it's too late.
Veridium's UBA framework identifies patterns of human behavior and applies statistical analysis to detect anomalies that could indicate potential threats. Veridium InMotion increases the reliability of all native biometrics for authentication by pairing behavioral data captured on smartphones with users' biometrics, making it more difficult for malicious actors to spoof their fingerprints or faces to gain access to corporate accounts.
"As data breaches and insider threats increasingly plague the enterprise, businesses are in need of a strong solution that can better recognize and verify users' identities," said Ionut Dumitran, Veridium's head of product development. “With user behavior analytics, a malicious actor that has someone’s phone and their fingerprints – or even similar facial features, like a twin might – will have an extremely difficult time trying to replicate their unique mannerisms. By tapping into the power of behavioral biometrics, Veridium InMotion can help businesses diminish the risk of identity as an attack vector and strengthen authentication in a way that is both transparent and frictionless for the user.”
Veridium InMotion is part of the VeridiumID platform, which captures how users interact with their smartphone. Each time a user authenticates their identity, his or her interactions are logged; after the first 10 authentications, a baseline that is specific to each user is established to compare future interactions. Suspicious movements that don’t align with previously recorded user behavior patterns are immediately reported and flagged to administrators who can evaluate the risk and potentially stop malicious activity in motion.
Key features of Veridium InMotion include:
- Motion detection: Veridium collects information from smartphone motion sensors (the accelerometer and the gyroscope) when the user initiates biometric authentication. No personal information is stored – only motion patterns.
- Machine learning: It requires just 10 authentications to get a baseline for most users. The model then continues to refine itself as it learns the user’s behavior.
- Confidence scores: Once a pattern of authentication is established, Veridium will rate the authentication with a confidence score. Based on risk factors, a low confidence score can initiate step-up authentication via SMS, email or phone, among others. In high-risk scenarios, a low confidence score and multiple failed attempts could initiate the blocking of a user completely.