#Typing Pattern Recognition Login System In this project we designed and implemented a login system that depends, not only on the correctness of the password, but also on the unique typing characteristics of the users. A common security problem is leaked passwords. Our system prevents this problem by making it very difficult to login just by knowing the correct password; the attacker must also be able to type it in the correct way, which is embedded into the muscle memory of the legitimate user.

The heart of the system there is a self-learning, fuzzy algorithm that takes into consideration the previous logins (keystroke timings, frequency of logins, etc.), and decides if the current login attempt is matching closely enough the legitimate user profile. The system can become so accurate that can distinguish between typing under normal conditions vs typing under emotional pressure (fear, stress, etc.), a characteristic that can be utilized in sensitive industrial and military systems. For example, it can prevent legitimate users from logging in, if they are subjected to emotional or physical force.

##Authors

• Lisa Ehrlinger - https://github.com/lisehr
• Kostas Konstantopoulos - https://github.com/kdop
• Panagiotis Nikoloutsopoulos - https://github.com/nikoloup

##License This project is released under the MIT License, see LICENSE.txt for more details.