  Footfall based biometric system is perhaps the only person identification
technique which does not hinder the natural movement of an individual. This is
a clear edge over all other biometric systems which require a formidable amount
of human intervention and encroach upon an individual's privacy to some extent
or the other. This paper presents a Fog computing architecture for implementing
footfall based biometric system using widespread geographically distributed
geophones (vibration sensor). Results were stored in an Internet of Things
(IoT) cloud. We have tested our biometric system on an indigenous database
(created by us) containing 46000 footfall events from 8 individuals and
achieved an accuracy of 73%, 90% and 95% in case of 1, 5 and 10 footsteps per
sample. We also proposed a basis pursuit based data compression technique DS8BP
for wireless transmission of footfall events to the Fog. DS8BP compresses the
original footfall events (sampled at 8 kHz) by a factor of 108 and also acts as
a smoothing filter. These experimental results depict the high viability of our
technique in the realm of person identification and access control systems.
