Preventing lunchtime attacks: fighting insider threats with eye movement biometrics by Eberz, S, Rasmussen, K, Lenders, V, Martinovic, I

“…We introduce a novel biometric based on distinctive eye movement patterns. The biometric consists of 21 features that allow us to reliably distinguish users based on differences in these patterns. …”

Preventing Lunchtime Attacks: Fighting Insider Threats With Eye Movement Biometrics by Eberz, S, Rasmussen, K, Lenders, V, Martinovic, I

28 blinks later: tackling practical challenges of eye movement biometrics by Eberz, S, Lovisotto, G, Rasmussen, K, Lenders, V, Martinovic, I

Preventing Lunchtime Attacks: Fighting Insider Threats With Eye Movement Biometrics by Eberz, S, Rasmussen, K, Lenders, V, Martinovic, I

“…We introduce a novel biometric based on distinctive eye movement patterns. The biometric consists of 21 features that allow us to reliably distinguish users based on differences in these patterns. …”

Looks like eve: exposing insider threats using eye movement biometrics by Eberz, S, Rasmussen, K, Lenders, V, Martinovic, I

“…We introduce a novel biometric based on distinctive eye movement patterns. The biometric consists of 20 features that allow us to reliably distinguish users based on differences in these patterns. …”

When your fitness tracker betrays you: quantifying the predictability of biometric features across contexts by Eberz, S, Lovisotto, G, Patanè, A, Kwiatkowska, M, Lenders, V, Martinovic, I

“…Overall, we observe that cross-context attacks on eye movements, mouse movements and touchscreen inputs are comparatively easy while ECG and gait exhibit much more chaotic cross-context changes.…”

Evaluating behavioral biometrics for continuous authentication: challenges and metrics by Eberz, S, Rasmussen, K, Lenders, V, Martinovic, I

“…We show that some biometrics (such as eye movements) are particularly prone to systematic errors, while others (such as touchscreen inputs) show more even error distributions. …”