Passwords are the most used method for user authentication and accessing sensitive information from the internet. The increased popularity of the internet has elevated cybercrimes and has promoted other malicious uses. Security frameworks, essentially biometric frameworks are being developed in response to ever-increasing security threats. An advantage of using behavioral biometrics over physiological biometrics is that it can be used for surveillance also. The behavioral biometric that uses typing patterns to identify a person is called keystroke dynamics. In keystroke dynamics, certain features are extracted that usually depend upon the time which the keys are held down and between latency of different keys. Keystroke dynamics is the most sought-after authentication protocol as it is non-disruptive in nature, affordable, and seamless integration with existing technology without additional hardware. However, user authentication by keystroke dynamics shows less precision as compared to other biometric techniques. Research has been conducted for data acquisition, feature selection, and classification by machine learning. The accuracy of keystroke biometrics is not equivalent too their biometric techniques such as hand geometry and iris recognition. Biomimetic nanotechnology- is a new discipline inside the region of nano structuring and especially nanorobotics. This is because user consistency and uniqueness are difficult to achieve in keystroke biometrics. Integration of keystroke biometrics with sensor technology for better accuracy is less explored. The aim of this paper is to provide an insight into nano technology and sensor technology used in Keystroke Dynamics.

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