DocumentCode :
238360
Title :
Mouse gesture based authentication using machine learning algorithm
Author :
Muthumari, G. ; Shenbagaraj, R. ; Blessa Binolin Pepsi, M.
Author_Institution :
Dept. of Inf. Technol., Mepco Schlenk Eng. Coll., Sivakasi, India
fYear :
2014
fDate :
8-10 May 2014
Firstpage :
492
Lastpage :
496
Abstract :
To authenticate a computer user, classification based on mouse operating behavior is proposed. It is used to perform the authentication task in initial login stage by capturing the mouse movements. The mouse operating behavior of users can be captured as coordinate axes and elapsed time, based on movement of the mouse. The obtained mouse behavior data consist of outliers and behavioral variability; these can be addressed by Peirce´s criterion and Weighted Least Square Regression (WLSR) respectively. The features are extracted from that mouse behavior data to categorize the user´s unique mouse behavior. The extracted features are analyzed and performs authentication using Learning Vector Quantization (LVQ). This LVQ Algorithm is used as a classifier, to find whether the given sample is authorized or unauthorized identity. The test result proves that, the proposed method WLSR with learning vector quantization classifier provides low error rates with good accuracy than the existing method.
Keywords :
authorisation; biometrics (access control); feature extraction; learning (artificial intelligence); pattern classification; regression analysis; vector quantisation; LVQ algorithm; Peirce´s criterion; WLSR; authorized identity; behavioral variability; computer user; feature extraction; initial login stage; learning vector quantization classifier; mouse gesture based authentication; mouse movements; mouse operating behavior; unauthorized identity; weighted least square regression; Biology; Classification algorithms; Quantization (signal); Regression tree analysis; Smoothing methods; Support vector machines; Visualization; Authentication; Outlier; mouse dynamics Weighted Least Square Regression;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Advanced Communication Control and Computing Technologies (ICACCCT), 2014 International Conference on
Conference_Location :
Ramanathapuram
Print_ISBN :
978-1-4799-3913-8
Type :
conf
DOI :
10.1109/ICACCCT.2014.7019492
Filename :
7019492
Link To Document :
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