A keystroke biometric system was enhanced to capture raw keystroke data directly from an individual’s computer system using an open source key logger originally designed for software testing. The key logger runs in the background capturing keystrokes directly from the operating system requiring no additional capture software, text entry window, or edit box for input. This allows the freedom to generate unrestricted entry from any application installed on a system. Long input data were collected from 20 participants using spreadsheet, browser, and text applications. Subjects were mainly students at the University and free to type whatever they desired without using copy tasks in any of these experimental scenarios. Short input data simulating a ten digit passcode were also collected from 30 participants each entering the same digit sequence strictly from the numeric keypad section of the keyboard. Verification experiments using novel approaches regarding feature sets and classification methods were run on both the unrestricted long input samples and static short passcode input. ROC curves were generated for each experiment using Equal Error Rate as the essential performance measure.
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Professionally I've been working in Information Technology for over 25 years in the areas of application development, data warehousing, and business intelligence. Academically I recently completed my research doctorate in keystroke biometrics focusing on intruder detection using long text input and passcode authentication using short numeric input.
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Taschenbuch. Zustand: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -A keystroke biometric system was enhanced to capture raw keystroke data directly from an individual's computer system using an open source key logger originally designed for software testing. The key logger runs in the background capturing keystrokes directly from the operating system requiring no additional capture software, text entry window, or edit box for input. This allows the freedom to generate unrestricted entry from any application installed on a system. Long input data were collected from 20 participants using spreadsheet, browser, and text applications. Subjects were mainly students at the University and free to type whatever they desired without using copy tasks in any of these experimental scenarios. Short input data simulating a ten digit passcode were also collected from 30 participants each entering the same digit sequence strictly from the numeric keypad section of the keyboard. Verification experiments using novel approaches regarding feature sets and classification methods were run on both the unrestricted long input samples and static short passcode input. ROC curves were generated for each experiment using Equal Error Rate as the essential performance measure. 184 pp. Englisch. Bestandsnummer des Verkäufers 9783659624285
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Taschenbuch. Zustand: Neu. Keystroke Biometric Studies on Short and Long Input Including Numerics | Intruder Detection using Keystroke Biometrics on Short Numeric Input and Long Text, Browser, and Spreadsheet Input | Ned Bakelman | Taschenbuch | 184 S. | Englisch | 2014 | LAP LAMBERT Academic Publishing | EAN 9783659624285 | Verantwortliche Person für die EU: BoD - Books on Demand, In de Tarpen 42, 22848 Norderstedt, info[at]bod[dot]de | Anbieter: preigu. Bestandsnummer des Verkäufers 105002829
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Taschenbuch. Zustand: Neu. This item is printed on demand - Print on Demand Titel. Neuware -A keystroke biometric system was enhanced to capture raw keystroke data directly from an individual's computer system using an open source key logger originally designed for software testing. The key logger runs in the background capturing keystrokes directly from the operating system requiring no additional capture software, text entry window, or edit box for input. This allows the freedom to generate unrestricted entry from any application installed on a system. Long input data were collected from 20 participants using spreadsheet, browser, and text applications. Subjects were mainly students at the University and free to type whatever they desired without using copy tasks in any of these experimental scenarios. Short input data simulating a ten digit passcode were also collected from 30 participants each entering the same digit sequence strictly from the numeric keypad section of the keyboard. Verification experiments using novel approaches regarding feature sets and classification methods were run on both the unrestricted long input samples and static short passcode input. ROC curves were generated for each experiment using Equal Error Rate as the essential performance measure.VDM Verlag, Dudweiler Landstraße 99, 66123 Saarbrücken 184 pp. Englisch. Bestandsnummer des Verkäufers 9783659624285
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Taschenbuch. Zustand: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - A keystroke biometric system was enhanced to capture raw keystroke data directly from an individual's computer system using an open source key logger originally designed for software testing. The key logger runs in the background capturing keystrokes directly from the operating system requiring no additional capture software, text entry window, or edit box for input. This allows the freedom to generate unrestricted entry from any application installed on a system. Long input data were collected from 20 participants using spreadsheet, browser, and text applications. Subjects were mainly students at the University and free to type whatever they desired without using copy tasks in any of these experimental scenarios. Short input data simulating a ten digit passcode were also collected from 30 participants each entering the same digit sequence strictly from the numeric keypad section of the keyboard. Verification experiments using novel approaches regarding feature sets and classification methods were run on both the unrestricted long input samples and static short passcode input. ROC curves were generated for each experiment using Equal Error Rate as the essential performance measure. Bestandsnummer des Verkäufers 9783659624285
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