Research Article

Smartwatch-Based Legitimate User Identification for Cloud-Based Secure Services

Table 1

Average accuracy for legitimate user identification with 400 samples per window.

SensorActivitiesClassifiers
DTSVMKNNNB

Acc.Walking0.9868 ± 0.00940.9391 ± 0.01810.9375 ± 0.01710.7616 ± 0.0201
Walking up0.8753 ± 0.03270.8005 ± 0.04220.7874 ± 0.03880.5876 ± 0.0540
Walking down0.8835 ± 0.03830.8447 ± 0.05340.7831 ± 0.05980.5619 ± 0.0909
Running0.8168 ± 0.03630.6381 ± 0.05540.5969 ± 0.04770.5311 ± 0.0325
Jogging0.9572 ± 0.01470.8816 ± 0.01630.9260 ± 0.02360.6234 ± 0.0384

Gyr.Walking0.9638 ± 0.01150.9177 ± 0.02680.9504 ± 0.00660.5149 ± 0.0367
Walking up0.8575 ± 0.03890.8362 ± 0.03330.8313 ± 0.01810.5423 ± 0.0683
Walking down0.8983 ± 0.04530.8062 ± 0.03390.8126 ± 0.02250.5476 ± 0.0595
Running0.8521 ± 0.06510.6737 ± 0.03900.7359 ± 0.02200.5866 ± 0.0483
Jogging0.9424 ± 0.01630.8964 ± 0.02720.8903 ± 0.00950.6629 ± 0.0376

Mag.Walking0.9193 ± 0.02080.7699 ± 0.02590.8551 ± 0.03390.6777 ± 0.0339
Walking up0.7600 ± 0.05490.5951 ± 0.04860.7107 ± 0.04050.5907 ± 0.0674
Walking down0.8298 ± 0.05430.7233 ± 0.04860.7055 ± 0.06710.5826 ± 0.0716
Running0.6384 ± 0.06110.5768 ± 0.03390.5916 ± 0.04810.3524 ± 0.0589
Jogging0.7056 ± 0.04610.4637 ± 0.04190.5873 ± 0.03610.3340 ± 0.0287