Secure techniques and methods for authenticating visually impaired mobile phone users

A series of new types of frauds and threats have emerged with the increased popularity of smartphones. Studies show that smartphone users are three times more likely to become the victims of identity fraud. Though researchers have developed many well known methods for user authentication in smartphone, little has been done focusing on visually impaired mobile device users. Commonly used username-password based authentication is not suitable for such users as it is cumbersome and highly susceptible to eavesdropping. In this paper, we have proposed a comprehensive algorithmic model for detecting different physical activities, such as walking, by analyzing the accelerometer sensor data from smartphones. Our proposed scheme proves that each person´s gait pattern is unique and can be used as a bio-metric data for authentication. The new tool promises to provide a feasible solution for authentication, especially for visually impaired smartphone users, free from aural and visual eavesdropping.