Biometric-rich gestures: a novel approach to authentication on multi-touch devices

By Napa Sae-Bae, Kowsar Ahmed, Katherine Isbister, Nasir D. Memon. International Conference on Human Factors in Computing Systems, 2012

331 citations recorded by the source corpus.

Subfields: Information Systems, Human-Computer Interaction, Signal Processing

View Paper: https://www.semanticscholar.org/paper/b7b2cda2c366cbb1b68ea30df68fce46f99f51ff

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Information Systems

1. Dawn Song
2. I. Martinovic
3. Yevgeni Koucheryavy
4. Aleksandr Ometov
5. Mario Frank
6. Haining Wang
7. Neil Zhenqiang Gong
8. Binghui Wang

In Signal Processing

1. Dawn Song
2. Sergey D. Andreev
3. I. Martinovic
4. Yevgeni Koucheryavy
5. Tommi J. Mikkonen
6. Aleksandr Ometov
7. Niko Mäkitalo
8. S. Bezzateev

Citations in the corpus

• Multi-Factor Authentication: A Survey (2018, methodology): “In case the MFA system is specifically developed for predefined gesture analysis [122], the user is required to replicate a previously learned movement while holding or wearing the sensing device [123–125].”
• You Are How You Touch: User Verification on Smartphones via Tapping Behaviors (2014, background): “[29] makes use of multi-touch screen sensor on iPad (not phone) to capture the palm movement.”
• Touchalytics: On the Applicability of Touchscreen Input as a Behavioral Biometric for Continuous Authentication (2012, background): “All data collected for this paper is available online 1 .”