  The massive explosion and ubiquity of computing devices and the outreach of
the web have been the most defining events of the century so far. As more and
more people gain access to the internet, traditional know-something and
have-something authentication methods such as PINs and passwords are proving to
be insufficient for prohibiting unauthorized access to increasingly personal
data on the web. Therefore, the need of the hour is a user-verification system
that is not only more reliable and secure, but also unobtrusive and
minimalistic. Keystroke Dynamics is a novel Biometric Technique; it is not only
unobtrusive, but also transparent and inexpensive. The fusion of keystroke
dynamics and Face Recognition engenders the most desirable characteristics of a
verification system. Our implementation uses Hidden Markov Models (HMM) for
modelling the Keystroke Dynamics, with the help of two widely used Feature
Vectors: Keypress Latency and Keypress Duration. On the other hand, Face
Recognition makes use of the traditional Eigenfaces approach.The results show
that the system has a high precision, with a False Acceptance Rate of 5.4% and
a False Rejection Rate of 9.2%. Moreover, it is also future-proof, as the
hardware requirements, i.e. camera and keyboard (physical or on-screen), have
become an indispensable part of modern computing.
