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Fuzzy inference for user identification of pressure-based keystroke biometrics

Keystroke biometrics belongs to the class of behavioral biometrics that is based on the user's typing rhythm when the user interacts with a keyboard — either to authenticate or identify the user. Identification of the users based on just their keystroke patterns captured from a keystroke biometrics system is discussed in this paper. The keystroke pattern generated is represented by the force applied on a numerical keypad and it is this set of features extracted from a common password that will be used to identify the users. The typing biometrics system had been designed and developed with an 8-bit microcontroller that is based on the AVR enhanced RISC architecture. These keystroke patterns from each user will form the inputs to the fuzzy inference system (FIS) that will identify the users. The results will be validated with 70% of the data as training and the remaining 30% for testing.