Thesis - Instituto de Telecomunicações

22 CHAPTER 2. STATE OF THE ARTAn early report on creating a system that could distinguish the users by the typewriterrhythms, was produced in 1975 [223]. An early study from Research ANd DevelopmentCorporation (RAND) [79], provided relevant information concerning the individuality traitof keystroke dynamics. The study was performed in a statistical analysis of seven secretariesin a long term evaluation. They were asked to type a list of paragraphs (all the secretarieswrote the same texts). The author established that the statistical distributions of the severaldigraphs were possible to use as an identity characteristic.The interest in keystroke dynamics as a new format for biometric identification can beenrecognized by the increasing number of publications and new approaches for biometric securitysystems. The International Committee for Information Technology Standards (INCITS)has already produced standardization guidelines for data format for keystroke dynamics [75].The document defines the format for interchange of keystroke data, containing informationrelated to the type of keyboard (standard, laptop, Person Digital Assistant (PDA)-keypador PDA-touchscreen, among other), and the keyboard country/layout identification.The techniques being proposed can be divided into two modes: short-code (log-in verification)and long-code (continuous verification). In the first case the user types his username and/or his password and the system uses this non-free text information to verify theuser identity [160]. In the continuous approach, the user is already in an authenticatedenvironment and continues to be monitored in a free-text approach. If the keystroke dynamicsvaries too much from the user model, the user can be asked for some other strongerbiometric information to regain access to the system [216].In both cases (short code and long code) the base features found in literature are thefollowing:1. the time between two consecutive keystrokes - latency;2. duration of the key pressed - hold-time;3. statistics from pairs of keys - digraph statistics.When more time is available to capture behavioral information from the key typingdynamics of the user, the following features are also extracted for continuous verification(long code) mode:1. statistics from consecutive key triplets - trigraph statistics;