Keystroke analysis of free text

By Daniele Gunetti, Claudia Picardi. TSEC, 2005

501 citations recorded by the source corpus.

Subfields: Information Systems, Signal Processing

View Paper: https://www.semanticscholar.org/paper/e9232edb4ec10313e17c27bd518cb5ffd4107a46

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. Michael Lippold
2. Regan L. Mandryk
3. Clayton Epp
4. Damon L. Woodard
5. Salil Banerjee

In Signal Processing

1. Michael Lippold
2. Regan L. Mandryk
3. Ernesto Damiani
4. Clayton Epp
5. Damon L. Woodard
6. Zhibo Zhang
7. Fatma Taher
8. Chan Yeob Yeun

Citations in the corpus

• Biometric Authentication and Identification using Keystroke Dynamics: A Survey (2012, methodology): “Gunetti & Picardi [61] 1,2 Relative, Abs.”
• Explainable Artificial Intelligence Applications in Cyber Security: State-of-the-Art in Research (2022, methodology): “[144] Torino 2005 607 Although the Orino dataset is similarly gathered using a predefined HTML form, participants are free to use any keyboard and complete their tasks at home rather than in a lab.”
• Identifying emotional states using keystroke dynamics (2011, methodology): “There have been fewer approaches [10,16,25] that use models based on free text (text that is not prescribed to the user), as they do not perform as well as fixed-text models [25].”
• HMOG: New Behavioral Biometric Features for Continuous Authentication of Smartphone Users (2015, unknown): “Early work in the field used keystroke dynamics [44]–[47] to authenticate desktop users.”