Auflistung nach Autor:in "Schuckers, Stephanie"
1 - 4 von 4
Treffer pro Seite
Sortieroptionen
- KonferenzbeitragFast and Accurate Continuous User Authentication by Fusion of Instance-based, Free-text Keystroke Dynamics(BIOSIG 2019 - Proceedings of the 18th International Conference of the Biometrics Special Interest Group, 2019) Ayotte, Blaine; Banavar, Mahesh K.; Hou, Daqing; Schuckers, StephanieKeystroke dynamics study the way in which users input text via their keyboards, which is unique to each individual, and can form a component of a behavioral biometric system to improve existing account security. Keystroke dynamics systems on free-text data use n-graphs that measure the timing between consecutive keystrokes to distinguish between users. Many algorithms require 500, 1,000, or more keystrokes to achieve EERs of below 10%. In this paper, we propose an instancebased graph comparison algorithm to reduce the number of keystrokes required to authenticate users. Commonly used features such as monographs and digraphs are investigated. Feature importance is determined and used to construct a fused classifier. Detection error tradeoff (DET) curves are produced with different numbers of keystrokes. The fused classifier outperforms the state-of-the-art with EERs of 7.9%, 5.7%, 3.4%, and 2.7% for test samples of 50, 100, 200, and 500 keystrokes.
- KonferenzbeitragFingerprint pore characteristics for liveness detection(BIOSIG 2014, 2014) Johnson, Peter; Schuckers, Stephanie
- KonferenzbeitragLongitudinal study of voice recognition in children(BIOSIG 2020 - Proceedings of the 19th International Conference of the Biometrics Special Interest Group, 2020) Purnapatra, Sandip; Das, Priyanka; Holsopple, Laura; Schuckers, StephanieSpeaker recognition as a biometric modality is on the rise in the consumer marketplace for banking, online services, and personal assistant services with a potential for wider application areas. Most current applications involve adults. One of the biggest challenges in speaker recognition for children is the change in the voice properties as a child age. This work proposes a baseline longitudinal dataset from the same 30 children in the age group of 4 to 14 years over a time frame of 2.5 years and evaluates speaker recognition performance in children with the available speaker recognition technology.
- KonferenzbeitragVerification of individuals from accelerometer measures of cardiac chest movements(BIOSIG 2013, 2013) Vural, Esra; Simske, Steven; Schuckers, StephanieBiometric verification is gaining popularity particularly for personal security during internet and mobile device usage. A novel approach for verification of individuals is proposed to measure mechanical cardiovascular activity through an accelerometer sensor placed on the surface of the chest above the sternum. Time frequency analysis methods are employed to evaluate biometric performance. Accelerometer measurements were acquired on two different sessions from ten subjects after delays ranging from 1 to 2 weeks. For individual subject verification, Gaussian mixture models were built per each individual and a background model was created for the remaining impostors. A likelihood ratio test with background model was employed for testing. In this study we found preliminary evidence for the use of the cardiovascular signal measured with an accelerometer placed on the sternum as a biometric sensor to verify individuals. Verification testing using this approach obtained a mean EER rate of 0.06 for inter-session testing.