Behavioral Biometrics¶
Definition¶
Behavioral biometrics identifies individuals based on patterns in their behavior — how they type, swipe, hold their phone, and interact with devices. Unlike physiological biometrics (face, fingerprint), behavioral biometrics provides continuous, passive authentication without requiring explicit user action.
Behavioral Signals¶
| Signal | What's Analyzed | eKYC Application |
|---|---|---|
| Keystroke dynamics | Typing speed, pressure, rhythm, flight time | Continuous authentication during form filling |
| Touch/swipe patterns | Pressure, speed, angle, gesture shape | Passive identity during app interaction |
| Device motion | Accelerometer/gyroscope patterns during hold | Distinguish human from bot/emulator |
| Mouse dynamics | Movement speed, click patterns, trajectory | Web-based verification |
| Navigation patterns | How user moves through app screens | Fraud detection during onboarding |
Role in eKYC¶
Behavioral biometrics complements face verification as an additional signal:
- During onboarding: detect bots, emulators, automated attacks
- Post-onboarding: continuous authentication without explicit re-verification
- Risk scoring: behavioral anomalies trigger step-up verification
Key Takeaways¶
Summary
- Behavioral biometrics provides passive, continuous identity assurance
- Complements face biometrics — adds a layer that deepfakes and injection attacks cannot easily replicate
- Most useful for ongoing authentication rather than initial onboarding
- Key providers: BioCatch, BehavioSec (LexisNexis), Callsign