User identification is paramount to guarantee the security of a web system.
However, classical information to identify users (e.g. user credentials or
browsing history) are not reliable enough. Biometrics
markers (e.g. keystroke patterns), on the other hand, represent a viable
reference to correctly identify users. These data can be
easily collected - no disruptive change in user experience - and can be
derived from users' interaction with the system.
In this talk I will present how Machine and Deep Learning techniques can be effectively used to learn unique identification markers from keystroke
behavioural patterns of users aiming to prevent user-account