@inproceedings{8a72c3b1fd774be181bc0ab75928f69c,
title = "Finger-drawn pin authentication on touch devices",
abstract = "PIN authentication is widely used thanks to its simplicity and usability, but it is known to be susceptible to shoulder surfing. In this paper, we propose a novel online finger-drawn PIN authentication technique that lets a user draw a PIN on a touch interface with her finger. The system provides some resilience to shoulder surfing without increasing authentication delay and complexity by using both the PIN as well as a behavioral biometric in user verification. Our approach adopts the Dynamic Time Warping (DTW) algorithm to compute dissimilarity scores between PIN samples. We evaluate our system in two shoulder surfing scenarios: 1) PIN attack where the attacker only knows the victim's PIN but has no information about it's drawing characteristic and 2) Imitation attack where an attacker has access to a dynamic drawing sequence of a victim's finger-drawn PIN in the form of multiple observations. Experimental results with a data set of 40 users and 2400 imitating samples from two attacks yield an Equal Error Rate (EER) of 6.7% and 9.9% respectively, indicating the need for further study on this promising authentication mechanism.",
keywords = "Finger-drawn PIN, behavioral biometric, mobile authentication, online signature, shoulder surfing",
author = "{Van Nguyen}, Toan and Napa Sae-Bae and Nasir Memon",
note = "Publisher Copyright: {\textcopyright} 2014 IEEE.",
year = "2014",
month = jan,
day = "28",
doi = "10.1109/ICIP.2014.7026013",
language = "English (US)",
series = "2014 IEEE International Conference on Image Processing, ICIP 2014",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "5002--5006",
booktitle = "2014 IEEE International Conference on Image Processing, ICIP 2014",
}