The present invention relates to an improved method of providing identification of a user or authentication of a user's identity. More particularly, the present invention relates to an improved method of providing identification of a user or authentication of a user's identity using conditional behavioural biometrics. The present invention seeks to provide an enhanced method of authenticating and/or identifying a user identity using conditional behavioural biometrics. According to a first aspect of the present invention, there is provided a method of generating a user profile for use in identifying and/or authenticating a user on a device, the device equipped with one or more sensors, the method comprising: generating a set of data points from sensory data collected by the one or more sensors; clustering the set of data points to produce a set of data clusters; developing a first classifier for the data clusters, the first classifier being operable to assign a further data point derived from a further user interaction with the computing device to one of the data clusters; and developing one or more further classifiers for at least one of the data clusters, the further classifier operable to identify and/or authenticate a user identity based on the further data point.
Please help me write a proper abstract based on the patent claims. CLAIM: 1. A method of generating a user profile for use in identifying and/or authenticating a user on a device, the device equipped with one or more sensors, the method comprising: generating a set of data points from sensory data collected by the one or more sensors; clustering the set of data points to produce a set of data clusters, wherein each data cluster corresponds to a respective user activity context; and developing a classifier for each of the data clusters, the classifier for each cluster operable to identify and/or authenticate a user based on a data point assigned to that cluster and derived from a user interaction with the device. 2. A method of identifying and/or authenticating a user on a device, the device equipped with one or more sensors, the method comprising: generating a data point from sensory data derived from a user interaction with the device; assigning the data point to one of a plurality of clusters of data points, wherein each of the data clusters corresponds to a respective user activity context; and applying a classifier to the data point, the classifier being chosen from a set of classifiers based on the assigned data cluster, and operable to identify and/or authenticate a user based on the data point. 3. A method according to claim 1, wherein the sensory data is collected during a plurality of user interactions with the device. 4. A method according to claim 1, wherein an algorithm is used to perform the clustering of the data points derived from the sensory data. 5. A method according to claim 4, wherein the algorithm is one or more clustering algorithms based on one of a K-means algorithm or a Gaussian Mixture Model using an Expectation-Maximisation algorithm. 6. A method according to claim 1, further comprising developing a cluster classifier for the data clusters, the cluster classifier being operable to assign a data point derived from a user interaction with the device to one of the data clusters 7. A method according to claim 1, wherein the identification and/or authentication of the user further comprises the step of authenticating the user identity using the classifier. 8. A method according to claim 2, wherein the output of the classifier is a confidence score in the user identity or authentication. 9. A method according to claim 8, wherein if the confidence score is below a pre-defined threshold, further identification and/or authentication steps are carried out or the user is not identified and/or authenticated. 10. A method according to claim 2, wherein each classifier in the set of classifiers is associated with a respective one of the plurality of clusters. 11. A method according to claim 2, wherein the step of assigning comprises using a cluster classifier developed from a plurality of previous user interactions with the device. 12. A method according to claim 1, wherein the device comprises at least one of: a mobile device; a local server; a cloud or network based server; and a desktop computer. 13. A method of identifying and/or authenticating a user on a device, the device equipped with one or more sensors, the method comprising: generating a data point from sensory data derived from a user interaction with the device; selecting a classifier in dependence on a user activity context identified from the data point; and applying the selected classifier to the data point so as to determine a confidence score for identifying and/or authenticating the user. 14. A method according to claim 1, wherein the user activity context comprises at least one of: a user location; a user activity; a user's movement; a user's speed; the device's connections or the device orientation. 15. A method according to claim 2, wherein the user activity context comprises at least one of: a user location; a user activity; a user's movement; a user's speed; the device's connections or the device orientation. 16. A method according to claim 13, wherein the user activity context comprises at least one of: a user location; a user activity; a user's movement; a user's speed; the device's connections or the device orientation. 17. A method according to claim 13, wherein if the confidence score is below a pre-defined threshold, further identification and/or authentication steps are carried out or the user is not identified and/or authenticated. 18. A computing device configured to perform the method of claim 1. 19. A computing device configured to perform the method of claim 2. 20. A computing device configured to perform the method of claim 13.