Paper Info
Title
Personal feature extraction via grip force sensors mounted on a mobile phone: authenticating the user during key-operation
Abstract
We propose an algorithm for authenticating the user of a mobile phone from the outputs of pressure sensors during key-operations such as button-pushes. While not intended to replace password identification, it does help in providing the service which is suitable for a user without any his/her specific action. For example, during user's entering key strokes. if a service cloud can recognize user-authentication by analyzing key strokes, then, it can find the optimal services based on the user preference. Our algorithm is based on a statistic probabilistic model based approach; it calculates the probability distribution of the temporal differential values of pressure by Kalman filtering. The captured sensory data is compared to predicted sensory data based on the probability distribution to judge whether the person making the key-operation is the registered owner or not. We implement the proposed system and subject it to feasibility experiments with 10 subjects; its user-authentication accuracy is quite good with a FAR-FRR error rate of only 10[%].
Year
DOI
Venue
2012
10.1145/2406367.2406404
MUM
Keywords
Field
DocType
optimal service,user preference,user-authentication accuracy,personal feature extraction,key stroke,feasibility experiment,grip force sensor,sensory data,mobile phone,service cloud,far-frr error rate,pressure sensor,probability distribution,kalman filter
Data mining,Authentication,Computer science,Word error rate,Event (computing),Kalman filter,Real-time computing,Feature extraction,Probability distribution,Human–computer interaction,Password,Mobile phone
Conference
Citations 
PageRank 
References 
0
0.34
7
Authors
4
Name
Order
Citations
PageRank
Toshiki Iso1626.49
Tsutomu Horikoshi25210.65
Masakatsu Tsukamoto301.01
Takeshi Higuchi400.34