Identifying Users Based on Use of Input Devices

Examensarbete för masterexamen

Please use this identifier to cite or link to this item: https://hdl.handle.net/20.500.12380/111601
Download file(s):
File Description SizeFormat 
111601.pdfFulltext2.06 MBAdobe PDFView/Open
Type: Examensarbete för masterexamen
Master Thesis
Title: Identifying Users Based on Use of Input Devices
Authors: Alongi, Gianfranco
Alexandersson, Erik
Abstract: The need for other security measures besides secret keywords has highlighted the possibility to base a biometric security system on input device patterns. This report explores the feasability of using mouse and keyboard biometry in an online security system. After examining prior work in this area, an online test environment was set up where subjects could remotely complete experiment sessions by interacting with a web-site. Artificial Neural Networks (ANN), k-Nearest Neighbor (k-NN) and Self Organizing Maps (SOM) were combined into profiles which predicted sample validity. A final system accuracy of 0.92% False Accept Rate (FAR) and 43.16% False Reject Rate (FRR) was achieved. The best profile in the system achieved a FAR of 0.8% and a FRR of 0.0%. When one of the 19 subjects was browsing the online test environment, the system could with an accuracy of 54.1% correctly identify the user. Examining the results, it is clear that data of a higher quality is needed and alternative collection methods should be explored. It seems feasible to recognize a registered user solely based on keyboard, mouse and browser variables.
Keywords: Datavetenskap (datalogi);Computer Science
Issue Date: 2009
Publisher: Chalmers tekniska högskola / Institutionen för data- och informationsteknik (Chalmers)
Chalmers University of Technology / Department of Computer Science and Engineering (Chalmers)
URI: https://hdl.handle.net/20.500.12380/111601
Collection:Examensarbeten för masterexamen // Master Theses



Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.