Keystroke Recognition

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ke Pattern Classification ▶ Keystroke Recognition

Keystroke Recognition N ICK B ARTLOW West Virginia University, Morgantown, WV, USA

▶ Non-linear Techniques for Dimension Reduction

Synonyms Behavioral biometrics; Keystroke dynamics; Keystroke pattern classification

Key Binding Definition ▶ Biometric and User Data, Binding of

Keypoints ▶ Local Image Features

Keystroke Dynamics ▶ Keystroke Recognition

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2009 Springer Science+Business Media, LLC

Keystroke recognition is a ▶ behavioral biometric which utilizes the unique manner in which a person types to verify the identity of an individual. Typing patterns are predominantly extracted from computer keyboards, but the information can potentially be gathered from any input device having traditional keys with tactile response (i.e., cellular phones, PDA’s, etc). Although other measurements are conceivable, patterns used in keystroke dynamics are derived mainly from the two events that make up a keystroke: the Key-Down and Key-Up. The Key-Down event takes place at the initial depression of a key and the Key-Up occurs at the subsequent release of that key. Various unique features are then calculated based on the intrakey and inter-key timing variations between these events. After feature extraction, a wide range of algorithms can be employed to establish whether the unique pattern confirms or denies the claimed identity.

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Keystroke Recognition

Introduction The earliest form of keystroke recognition emerged in the early 1900s during the days of World War I. During the war, the French used listening posts in which operators were able to recognize the ‘‘fist’’ of enemy radio operators communicating in Morse code. These trained individuals would learn to recognize operators by differing lengths of pauses, dots and slashes, and varying transmission speeds. This intelligence subsequently allowed the French to establish the identity of entities such as enemy battalions. Far more sophisticated than electromechanical telegraphs used to transmit Morse code, keyboards of today offer many more opportunities to establish the unique manner in which one types. Intuitively, coarse level differentiation can be achieved by investigating typing speeds. For instance, a professional typist who averages 90 or more words per minute would be easily distinguished from a ‘‘hunt and peck’’ amateur who averages only 20–25 words per minute. That said, this feature only goes so far as many people type at similar speeds and the average speed that an individual types can vary significantly depending on many factors. The time it takes an individual to locate a key (sometimes referred to as ‘‘seek-time’’) also varies from key to key. For instance, left-handed individuals may have quicker seek-times for keys on the left side of the keyboard and vice versa [1]. Along those same lines, use of the shift keys to modify characters can also vary from individual based on handedness and typing skill. Trained professionals will always modify characters on the right side of the keyboard with the left