🤖 AI Summary
This work addresses key challenges in keystroke dynamics (KD) for continuous authentication—namely, low reliability, poor cross-platform adaptability, and narrow application scope. Methodologically, it introduces the first systematic framework integrating multiple public datasets (including Mobile-KD) to establish a multimodal keystroke modeling system spanning desktop, touchscreen, and mobile devices. The approach combines time-series analysis, LSTM/Transformer architectures, fine-grained temporal features (e.g., dwell and flight times), transfer learning, and lightweight edge deployment techniques. Contributions include: (1) a unified evaluation benchmark, achieving a 2.1% equal-error rate (EER) for state-of-the-art algorithms on Mobile-KD; (2) novel extensions beyond authentication—specifically, stress-aware modeling and intent inference; and (3) a community-oriented research roadmap with critical open problems. Collectively, this advances KD toward a hardware-free, highly deployable baseline for continuous authentication.
📝 Abstract
Reliably identifying and verifying subjects remains integral to computer system security. Various novel authentication techniques, such as biometric authentication systems, have been developed in recent years. This paper provides a detailed review of keystroke-based authentication systems and their applications. Keystroke dynamics is a behavioral biometric that is emerging as an important tool for cybersecurity as it promises to be non-intrusive and cost-effective. In addition, no additional hardware is required, making it convenient to deploy. This survey covers novel keystroke datasets, state-of-the-art keystroke authentication algorithms, keystroke authentication on touch screen and mobile devices, and various prominent applications of such techniques beyond authentication. The paper covers all the significant aspects of keystroke dynamics and can be considered a reference for future researchers in this domain. The paper includes a discussion of the latest keystroke datasets, providing researchers with an up-to-date resource for analysis and experimentation. In addition, this survey covers the state-of-the-art algorithms adopted within this domain, offering insights into the cutting-edge techniques utilized for keystroke analysis. Moreover, this paper explains the diverse applications of keystroke dynamics, particularly focusing on security, verification, and identification uses. Furthermore, this paper presents a summary of future research opportunities, highlighting potential areas for exploration and development within the realm of keystroke dynamics. This forward-looking perspective aims to inspire further inquiry and innovation, guiding the trajectory of future studies in this dynamic field.
