Keystroke dynamics based biometric authentication: A hybrid classifier approach

The increased use of computers in our day to day activities has marked the necessity to develop efficient methods of user identification for authentication purposes. The tasks of utmost importance are becoming dependent on computers for their completion. Under such circumstances it is essential that the whole process is least susceptible to breaches. The ease of accessibility and availability of keyboards in a computer system make it an economical source to generate characteristic biometric data. Therefore, keystroke dynamics has become a topic of research interest in recent times. Despite the huge potential keystroke dynamics has, there are a few shortcomings in the prevalent approaches that need to be addressed. The current accuracy measures prevent this method from being accepted as an industry standard. Furthermore, in some cases the computational time required to train a model before deployment becomes so large that it is virtually impossible to use such algorithms in daily life. The model proposed in this paper tries to overcome these drawbacks and improves upon the current performance measures.