Examining a Large Keystroke Biometrics Dataset for Statistical-Attack Openings
Abstract
Research on keystroke-based authentication has traditionally assumed human impostors who generate forgeries by physically typing on the keyboard. With bots now well understood to have the capacity to originate precisely timed keystroke sequences, this model of attack is likely to underestimate the threat facing a keystroke-based system in practice. In this work, we investigate how a keystroke-based authentication system would perform if it were subjected to synthetic attacks designed to mimic the typical user. To implement the attacks, we perform a rigorous statistical analysis on keystroke biometrics data collected over a 2-year period from more than 3000 users, and then use the observed statistical traits to design and launch algorithmic attacks against three state-of-the-art password-based keystroke verification systems.
Document Details
- Document Type
- Pub Defense Publication
- Publication Date
- Sep 01, 2013
- Source ID
- 10.1145/2516960
Entities
People
- Abdul Serwadda
- Vir V. Phoha
Organizations
- Air Force Office of Scientific Research
- Louisiana Tech University