The present-day world is filled with numerous valuable personal digital devices that need to be well safe-guarded. To see ample of U.S populace still suffering in the hands of impostors and fraudsters of different kinds, despite technological advancement in such great nation is worrisome. Other nations are not spared of this security menace and perpetrators. Cases of break-in of keyboard embedded or plugged-in devices become alarming day-in-day-out [8]. Many authentication mechanisms’ failures in vital devices like smartphones, tablets and laptops have been reported recently. PIN, which stands for Personal Identification Numbers and pattern drawing have been used frequently as authentication methods, especially on devices that use keyboards [6]. However, these devices are still susceptible to shoulder surfing occurrence [6]. Alternatively, keystroke dynamics which authenticates genuine owners of these devices, based on their typing manner has been studied for many years, but less utilized in these very important gadgets. Keystroke dynamics can help more in reducing these authentication problems being faced by these owners, by examining the password typed or patterns made, more essentially with how a user types (the time speed and all others) [6].

Keystroke dynamics Authentication Security Privacy Password Biometric R RStudio