1. A computer implemented method for identifying a user as one from a series of authorized users from free typed text, comprising the steps of (1) retrieving with a processor 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 text characters from a text input terminal, where said received test typing sample comprises a string of text characters that is not a fixed string of text characters; (3) extracting with a processor 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) selecting one of said authorized user profiles U k , and for said selected authorized user profile, determining which features in said selected authorized user profile are common with said extracted subset of features Z, and comparing said common extracted feature test values to said common selected authorized user typing profiles feature trial values to derive a selected authorized user score associated with said selected authorized user, wherein said selected authorized user score, is related to either (a) a conditional probability estimate P ⁡ ( U k / Z ) = P ⁡ ( U k / Z 1 , Z 2 , … ⁢ , Z n ) = P ⁡ ( U k ) P ⁡ ( Z 1 , Z 2 , … ⁢ , Z n ) ⁢ ∏ j = 1 n ⁢ ⁢ ( ∏ t = 1 m j ⁢ ⁢ P ⁡ ( z j t / U k ) ) , that the selected authorized user U k generated the test values associated with said set of extracted subset of features Z=(Z 1 , . . . Z n ) where each Z j vector consists of feature values z j 1 , z j 2 , . . . z j m j , where (i) subscript j refers to a j th feature, (ii) superscript m j represents the total number of times feature value for the j th feature is recorded in the vector Z j , and (iii) z j t represents the extracted test value for the j th feature at the t th component position in the Z j vector; or (b) an estimated similarity S k of said extracted features Z to the corresponding selected authorized user profile, wherein said estimated similarity S k to said selected authorized user U k is related to the proportion of (i) the total of all extracted feature test values that lie in a predetermined neighborhood of the corresponding feature trial values in said selected authorized user U k authorized user profile, to (ii) the total of all extracted feature test values for said selected authorized user; and (5) associating said test typing sample with said selected authorized user if said selected authorized user score satisfies a predefined condition.
2. The computer implemented method of claim 1 wherein said selected authorized user score fails to satisfy said predefined condition, and the method further comprises selecting another of said authorized user profiles, and repeating steps (4) and (5) using said selected another of said authorized user profiles to derive a score associated with said selected another of said authorized user profiles and testing said another authorized user score against said predefined condition and associating said test typing sample with said selected another authorized user if said selected another authorized user score satisfies a predefined condition.