ANJALI K K
MUHAMMED ALI
SHAMILY GEORGE
ANUSHA K R

The aim of our project is to automatically recognizing the identity of individuals by
machine learning. Biometric authentication is individual characteristics that cannot be
used by imposter to penetrate secure system. Keystroke dynamics based authentication
verifies user from their typing pattern. To authenticate user based on their typing
samples, it is required to find out he resemblance of a typing samples of user regardless
of the text typed. Key event timing is extracted from key features Latency, Dwell time,
Key interval, Up to up, Flight time and standard are measure in the form of FAR, FRR
and ER. For authentication, an input will be checked against the profiles within the
cluster which has significantly reduced the verification load.