Stationary mobile behavioral biometrics: A survey. Issue 128 (May 2023)

• Record Type: Journal Article
• Authors: Ray-Dowling, Aratrika; Hou, Daqing; Schuckers, Stephanie
• Is Part Of: Computers & security. Issue 128(2023)
• Publication Date: 2023-05
• Subjects: Mobile device security -- Continuous authentication -- Stationary behavioral biometrics -- Motion sensor -- Cognitive psychology -- Natural behavior -- Designed behavior; Computer security -- Periodicals; Electronic data processing departments -- Security measures -- Periodicals; 005.805
• DOI: 10.1016/j.cose.2023.103184
• Languages: English
• ISSNs: 0167-4048

Abstract

Highlights: Surveys the studies in stationary (sitting, standing) mobile behavioral biometrics. Categorizes user behaviors across studies into natural and designed. Describes the underpinning of behavioral biometrics in cognitive psychology. Categorizes studies into three groups based on usage of motion and other modalities. Characterizes each study along dimensions such as task, modality, and performance. Abstract: Current security mechanisms in mobile devices such as PINs, passwords, patterned passwords, and biometrics are one-time entry-point authentication and vulnerable to attacks. Furthermore, advanced mechanisms like Multi-Factor Authentication (MFA) introduce friction in the user experience. In contrast, behavioral biometrics rely on user interaction with computing devices to authenticate a user and thus, can be continuous, non-intrusive, and cost-effective, representing a promising direction that complements existing authentication techniques. This survey focuses on stationary/non-walking (sitting, standing) mobile behavioral biometrics through motion events like acceleration, gyroscope, magnetometer, and orientation (rotation) with the optional support of other non-motion, sporadic modalities such as swipes and keystrokes. The focus on stationary behaviors can be justified because such behaviors represent the major way a user interacts with mobile devices. To help readers understand the broad landscape of user activities/behaviors, we categorize the state of the art into natural and designed behaviors and describe the underpinning of behavioral biometrics in cognitive psychology. Furthermore, we categorize the surveyed studies into three groups based on the fusion of motion modalities and characterize each study along dimensions such as task, datasets, modality, algorithms, and performance. Based on our survey, we identify several future directions of research.