Implementation of distance metric between two samples of keystroke dynamics

Keystroke dynamic is one of the behavioral biometric identification techniques which distinguish users through their unique typing style. This paper presents two techniques to measure the distance metric between two samples of the same user. Two methods are used to implement the normalized distance between two samples of the same user; first method uses JavaScript for measuring the feature extraction between the user keystroke then uses the hardware for sorting and implementation the normalized distance using Xilinx Spartan-3E-XC3S1600E on a FPGA with VHDL by Xilinx tool ISE Web Pack 9.2i. Second method uses the JavaScript to capture the feature extraction timing information then sorting them ascending according to times then uses the hardware to calculate only the normalized distance. Comparison between two methods is discussed to choose the better method regarding the area data, time, and PAR report.