TY - GEN
T1 - Biometric-rich gestures
T2 - 30th ACM Conference on Human Factors in Computing Systems, CHI 2012
AU - Sae-Bae, Napa
AU - Ahmed, Kowsar
AU - Isbister, Katherine
AU - Memon, Nasir
PY - 2012
Y1 - 2012
N2 - In this paper, we present a novel multi-touch gesture-based authentication technique. We take advantage of the multitouch surface to combine biometric techniques with gestural input. We defined a comprehensive set of five-finger touch gestures, based upon classifying movement characteristics of the center of the palm and fingertips, and tested them in a user study combining biometric data collection with usability questions. Using pattern recognition techniques, we built a classifier to recognize unique biometric gesture characteristics of an individual. We achieved a 90% accuracy rate with single gestures, and saw significant improvement when multiple gestures were performed in sequence. We found user ratings of a gestures desirable characteristics (ease, pleasure, excitement) correlated with a gestures actual biometric recognition ratethat is to say, user ratings aligned well with gestural security, in contrast to typical text-based passwords. Based on these results, we conclude that multi-touch gestures show great promise as an authentication mechanism.
AB - In this paper, we present a novel multi-touch gesture-based authentication technique. We take advantage of the multitouch surface to combine biometric techniques with gestural input. We defined a comprehensive set of five-finger touch gestures, based upon classifying movement characteristics of the center of the palm and fingertips, and tested them in a user study combining biometric data collection with usability questions. Using pattern recognition techniques, we built a classifier to recognize unique biometric gesture characteristics of an individual. We achieved a 90% accuracy rate with single gestures, and saw significant improvement when multiple gestures were performed in sequence. We found user ratings of a gestures desirable characteristics (ease, pleasure, excitement) correlated with a gestures actual biometric recognition ratethat is to say, user ratings aligned well with gestural security, in contrast to typical text-based passwords. Based on these results, we conclude that multi-touch gestures show great promise as an authentication mechanism.
KW - Authentication
KW - Behavior biometric
KW - Multi-touch gestures
KW - Multi-touch interfaces
KW - Password
UR - http://www.scopus.com/inward/record.url?scp=84862081075&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84862081075&partnerID=8YFLogxK
U2 - 10.1145/2207676.2208543
DO - 10.1145/2207676.2208543
M3 - Conference contribution
AN - SCOPUS:84862081075
SN - 9781450310154
T3 - Conference on Human Factors in Computing Systems - Proceedings
SP - 977
EP - 986
BT - Conference Proceedings - The 30th ACM Conference on Human Factors in Computing Systems, CHI 2012
Y2 - 5 May 2012 through 10 May 2012
ER -