The BeiHang Keystroke Dynamics Authentication System
Juan Liu, Baochang Zhang, Linlin Shen, Jianzhuang Liu, Jason Zhao

TL;DR
This paper presents a comprehensive keystroke dynamics authentication system with an embedded device, online platform, new datasets, feature extraction method, and benchmark comparisons of classification algorithms.
Contribution
It introduces an embedded device and online system for keystroke authentication, along with new datasets and benchmark results for multiple classifiers.
Findings
Gabor filter bank effectively characterizes keystroke dynamics
Benchmark results for SVM, Gaussian, and nearest neighbor classifiers
Public databases promote keystroke authentication research
Abstract
Keystroke Dynamics is an important biometric solution for person authentication. Based upon keystroke dynamics, this paper designs an embedded password protection device, develops an online system, collects two public databases for promoting the research on keystroke authentication, exploits the Gabor filter bank to characterize keystroke dynamics, and provides benchmark results of three popular classification algorithms, one-class support vector machine, Gaussian classifier, and nearest neighbour classifier.
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
Taxonomy
TopicsUser Authentication and Security Systems · Biometric Identification and Security · Hand Gesture Recognition Systems
