Design and evaluation of a pressure based typing biometric authentication system
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Date
2011-10-21
Journal Title
Journal ISSN
Volume Title
Publisher
IntechOpen
Abstract
Although a variety of authentication devices to verify a user’s identity are in use today for
computer access control, passwords have been and probably would remain the preferred
method. Password authentication is an inexpensive and familiar paradigm that most
operating systems support. However, this method is vulnerable to intruder access. This is
largely due to the wrongful use of passwords by many users and to the unabated simplicity
of the mechanism which makes such system susceptible to unsubstantiated intruder attacks.
Methods are needed, therefore, to either enhance or reinforce existing password
authentication techniques.
There are two possible approaches to achieve this, namely by measuring the time between
consecutive keystrokes “latency” or measuring the force applied on each keystroke. The
pressure-based biometric authentication system (PBAS) has been designed to combine these
two approaches so as to enhance computer security. PBAS employs force sensors to measure
the exact amount of force a user exerts while typing. Signal processing is then carried out to
construct a waveform pattern for the password entered. In addition to the force, PBAS
measures the actual timing traces, which are often referred to as “latency”.
Two approaches to construct user typing pattern have been implemented with PBAS. First
approach utilizes a waveform acquired for user keystroke pressure along with time between
each keystroke “latency“ to create a unique user password typing pattern for authentication.
An auto-regressive (AR) classifier is used for the pressure pattern, while a latency classifier
is used for the time between keystrokes. The results of both classifiers are combined to
authenticate the user typing pattern.
The second approach combines the pressure and latency by creating a pattern of peak
keystroke force and latency. By combining the force and time features other classifiers have
been tested with PBAS, namely support vector machines (SVM), artificial neural network
(ANN), adaptive neuro-fuzzy inference system (ANFIS). Figure 1 illustrates how these
classifiers are integrated to develop the system.
As compared to conventional keystroke biometric authentication systems, PBAS has
employed a new approach by constructing a waveform pattern for the keystroke password.
This pattern provides a more dynamic and consistent biometric characteristics of the user. It
also eliminates the security threat posed by breaching the system through online network as
the access to the system is only possible through the pressure sensor reinforced keyboard
“biokeyboard”.
Description
Keywords
Pressure based typing, Biometric authentication system
Citation
Salami, M. J., Eltahir, W., & Ali, H. (2011). Design and evaluation of a pressure based typing biometric authentication system. In Biometric Systems, Design and Applications. IntechOpen.