Validating a user's identity is one of the fundamental security requirements in cyberspace. Current authentication approaches require people to create and remember secret credentials such as complex passwords, or to possess special hardware authentication tokens. Both are vulnerable to being compromised, or illegally shared. Even worse, authentication is typically supported solely at the start of a session. Recent developments in biometric authentication aim to overcome these challenges, but are either easy to bypass (e.g., imposter attacks), incapable of satisfactory false-positive-false-negative tradeoffs, or require expensive dedicated equipment. To address these weaknesses, the objective of this project is to develop a non-traditional approach to biometric authentication, which exploits motor learning and visual-motor adaptation to provide secure, effective and continuous human-user authentication. This project focuses on developing a new paradigm in cyber security - expertise-based continuous biometric authentication. The uniqueness of the new paradigm is to actively train the subject to achieve continuous authentication, by inducing a specific expertise into a human subject's interaction with a machine. An expertise is defined as an artificially-induced interaction pattern that is unique to the human subject. Once the subjects have been exposed to specific stimuli and learned their expertise, their behaviors are easily differentiable as long as the stimuli are maintained. To enhance the security of the system, as well as to preserve user privacy (by facilitating expertise fade-out after the cessation of the stimuli), the induced expertise are not static, but rather continuously evolving between randomly-chosen targets. The project develops expertise-based active biometric authentication modalities based on keyboard, mouse, and touchscreen devices. The outcome of this research shall have broader impacts on the nation's higher education, high-tech industries, and government. The research enhances the PIs' curriculum developments and helps attract, recruit and retain engineering students and broaden the participation of under-represented minorities and women in engineering programs. It also supports the PIs to outreach to talented college and high-school students and motivate them to study and eventually pursue Doctoral degrees in computer engineering areas.
SBE: Small: Continuous Human-User Authentication by Induced Procedural Visual-Motor Biometrics