A processor implemented method, comprising: obtaining, from a Global Positioning System, GPS, GPS data comprising trip information pertaining to a vehicle being driven by a driver; extracting one or more features from the trip information; ranking, using a ranking technique, the one or more extracted features from the trip information to selectively identify and obtain a set of one or more relevant features, wherein the one or more relevant features are selectively identified based the comparison between the one or more extracted features of the trip information, features of trip information pertaining to other drivers and historical data comprising driving patterns of the driver to be authenticated stored in a database, and based on a unique driver identifier obtained from the trip information; performing a second comparison of (i) the value of each relevant feature from the set of relevant features and (ii) a value of the corresponding feature pertaining to the one or more driving patterns stored in the database; generating abnormality scores for the set of relevant features based on the second comparison; and authenticating the driver based on the abnormality scores, wherein the step of extracting the one or more features from the trip information comprises: obtaining a primary data from the trip information, and deriving a secondary data from the primary data; and computing a respective first difference and a respective second difference for each primary data and derived secondary data, wherein the first and second differences form parameters of the journey; and computing one or more statistics for each of the parameters of the journey, wherein the statistics comprise mean, median, skewness, kurtosis, standard deviation, max, min, 97.5th percentile, Q3, Q1, 2.5th percentile, and wherein the one or more statistics form the one or more extracted features. obtaining, from a Global Positioning System, GPS, GPS data comprising trip information pertaining to a vehicle being driven by a driver; extracting one or more features from the trip information; ranking, using a ranking technique, the one or more extracted features from the trip information to selectively identify and obtain a set of one or more relevant features, wherein the one or more relevant features are selectively identified based the comparison between the one or more extracted features of the trip information, features of trip information pertaining to other drivers and historical data comprising driving patterns of the driver to be authenticated stored in a database, and based on a unique driver identifier obtained from the trip information; performing a second comparison of (i) the value of each relevant feature from the set of relevant features and (ii) a value of the corresponding feature pertaining to the one or more driving patterns stored in the database; generating abnormality scores for the set of relevant features based on the second comparison; and authenticating the driver based on the abnormality scores, wherein the step of extracting the one or more features from the trip information comprises: obtaining a primary data from the trip information, and deriving a secondary data from the primary data; and computing a respective first difference and a respective second difference for each primary data and derived secondary data, wherein the first and second differences form parameters of the journey; and computing one or more statistics for each of the parameters of the journey, wherein the statistics comprise mean, median, skewness, kurtosis, standard deviation, max, min, 97.5th percentile, Q3, Q1, 2.5th percentile, and wherein the one or more statistics form the one or more extracted features. obtaining a primary data from the trip information, and deriving a secondary data from the primary data; and computing a respective first difference and a respective second difference for each primary data and derived secondary data, wherein the first and second differences form parameters of the journey; and computing one or more statistics for each of the parameters of the journey, wherein the statistics comprise mean, median, skewness, kurtosis, standard deviation, max, min, 97.5th percentile, Q3, Q1, 2.5th percentile, and wherein the one or more statistics form the one or more extracted features.