Records the keystroke timing data and creates a model. Applies learning algorithms to differentiate between a valid user and an intruder. Biometrics based on “who” is the person or “how” the person behaves, present a significant security advancement to meet new challenges of security.
The most promising approach has been Keystroke Biometrics which refers to the habitual patterns or rhythms an individual exhibits while typing on a keyboard input device. Compared to other biometric schemas, keystroke has the primary advantages that:
- No external hardware like scanner or detector is needed. All that is wanted is a keyboard.
- The rhythm or the pattern of the users is a very reliable statistic.
- It can easily be deployed in conjunction with existing authentication systems.
- Front end : HTML 5+ CSS3+ Bootstrap+ Jquery for designing and styling and JavaScript for front-end validations
- Backend : PHP + Mysql for recording the keystrokes and collecting the registration and login mechanism.
- Database : MySQL to store User ID’s and passwords and also to hold session info.
- Machine Learning/ Statistical Modelling: R
- Manhatten Mean : Simple model, fixed threshold, not robust
- Euclidean Mean : Adaptible model, dynamic thresholding, less robust
- Manhatten Median : Simple model, fixed threshold, robust