A Modular Approach to Haptics and Security - A Preliminary Report

Computer Security within any organisation is a genuine concern. Username-password combinations have been used since 1961 to log into systems and, though methods such as cryptography can then be used to conceal the information, strong authentication remains a challenge. For example users tend to share or forget passwords or use the same password for many applications. A Haptics device allows the user to touch the virtual surface presented in a computer interface. Using such a device allows key (behavioural) biometrics features to be extracted. This data can then be analysed and used to authenticate the user. This paper proposes the use of a Haptic-password system which allows the employee (or the customer) to draw a predefined character on a screen so that key features can be extracted and matched to a stored template. Force feedback provided by the Haptics device is able to strengthen other behavioural biometric features extracted. This can be done with great accuracy (FAR 2.9% and FRR 3.9% using a Neural Network classifier). This system can potentially be used to aggregate all username-password combinations required for different applications at home or in the workplace. This research has potential in the fields of Biometric Security and Anomaly Detection as well as Smart Sensors and efficient Human Machine Interface (HMI)