1. A method for identifying a user as one from a series of authorized users from free typed text, comprising the steps of (1) retrieving stored typing profiles for a series of authorized users {U k } from a data storage device, each authorized user typing profile associated with a single authorized user and containing a set of trial values derived from feature measured values from said trial typing sample received from said associated authorized user, each of said trial values being associated with one feature from a set of predefined features {Z i }; (2) receiving a test typing sample of free alpha-numeric text from a text input terminal, where said free alpha-numeric text comprises a string of text characters that is not a fixed string of text characters; (3) extracting a subset of features Z from said received test typing sample, each extracted feature Z i in said subset Z having a set of non null test values derived from said extracted feature; (4) then for each authorized user profile, determining which features in said associated authorized user profile are common with said extracted features, and comparing said common extracted feature test values to said common authorized user typing profiles feature trial values to derive an authorized user score associated with said authorized user, wherein said authorized user score, for each authorized user U k , is proportional to a conditional probability estimate, P(U k /Z) that the authorized user U k generated the test values associated with said set of extracted features Z; (5) associating said test typing sample with one of said authorized users based on said authorized user scores, or with none of said authorized users if all of said authorized user test scores fail a predetermined test.
1. A method for identifying a user as one from a series of authorized users from free typed text, comprising the steps of (1) retrieving stored typing profiles for a series of authorized users {U k } from a data storage device, each authorized user typing profile associated with a single authorized user and containing a set of trial values derived from feature measured values from said trial typing sample received from said associated authorized user, each of said trial values being associated with one feature from a set of predefined features {Z i }; (2) receiving a test typing sample of free alpha-numeric text from a text input terminal, where said free alpha-numeric text comprises a string of text characters that is not a fixed string of text characters; (3) extracting a subset of features Z from said received test typing sample, each extracted feature Z i in said subset Z having a set of non null test values derived from said extracted feature; (4) then for each authorized user profile, determining which features in said associated authorized user profile are common with said extracted features, and comparing said common extracted feature test values to said common authorized user typing profiles feature trial values to derive an authorized user score associated with said authorized user, wherein said authorized user score, for each authorized user U k , is proportional to a conditional probability estimate, P(U k /Z) that the authorized user U k generated the test values associated with said set of extracted features Z; (5) associating said test typing sample with one of said authorized users based on said authorized user scores, or with none of said authorized users if all of said authorized user test scores fail a predetermined test. 7. The method of claim 1 wherein each said feature comprises a specific pair of adjacent alpha-numeric letters.