HMOG: New Behavioral Biometric Features for Continuous Authentication of Smartphone Users

By Zdenka Sitova, Jaroslav Sedenka, Qing Yang, Ge Peng, Gang Zhou, Paolo Gasti, K. Balagani. IEEE Transactions on Information Forensics and Security, 2015

383 citations recorded by the source corpus.

Subfields: Biomedical Engineering, Information Systems, Human-Computer Interaction

View Paper: https://www.semanticscholar.org/paper/b8d9406d2108ee92b6543d3d8505711716a8a179

How researchers see this paper

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

In Biomedical Engineering

1. Graham W. Taylor
2. Christian Wolf
3. Dhanesh Ramachandram
4. Natalia Neverova

In Information Systems

1. Graham W. Taylor
2. Deepak Chandra
3. Brandon Barbello

In Human-Computer Interaction

1. Graham W. Taylor
2. Christian Wolf
3. Deepak Chandra
4. Brandon Barbello
5. Dhanesh Ramachandram
6. Natalia Neverova

Citations in the corpus

• Learning Human Identity From Motion Patterns (2015, background): “In recent years, researchers in different fields have been working on creating fast and secure authentication alternatives that would make it possible to remove this burden from the user [6], [29].”
• Deep Multimodal Learning: A Survey on Recent Advances and Trends (2017, background): “The ubiquity of mobile smartphones, which have no fewer than ten sensors, has given rise to novel applications that involve multimodal data such as continuous biometric authentication [12] and activity recognition [13].”