Gait authentication using a cell phone based accelerometer sensor offers an unobtrusive, user-friendly, and periodic way of authenticating individuals on their cell phones. In this study, we present an approach to deal with inevitable errors induced by continuously changing sensor orientation and other noise under a realistic scenario (when the phone is placed inside the trouser pockets and the user is walking) by using the magnitude data of tri-axes accelerometer and wavelet based noise elimination modules. This study utilizes a gait data set of 35 participants collected at their respective normal walking pace in two different sessions with an average gap of 25 days between the sessions.