DocumentCode
1862762
Title
PAAKL: Password Authentication Using Behavioral Metrics
Author
Toptsis, Anestis A. ; Majonis, Joshua
Author_Institution
Dept. of Comput. Sci. & Eng., York Univ., Toronto, ON, Canada
fYear
2010
fDate
19-23 July 2010
Firstpage
351
Lastpage
356
Abstract
We present PAAKL, a method for password authentication. In addition to checking for a password´s correctness, PAAKL performs authentication by verifying that password using behavioral metrics extracted from the typing style of the rightful owner of a computer account. As such, PAAKL will deny access to users who have knowledge of a password but their typing style of that password is different from the typing style of the rightful owner. We implement and test our method with actual users. Our results indicate that the rightful owners of a password self-authenticate 92.5% of the time while the intruders - users that know the password of a rightful owner but are not rightful owners themselves, have 0% success in gaining access to a system.
Keywords
authorisation; behavioural sciences; software agents; PAAKL; artificial k-line; behavioral metrics; computer account; password authentication; rightful owner; typing style; user access denied; Artificial intelligence; Artificial neural networks; Authentication; Companies; Delay; Pattern matching; Training; Artificial K-lines; Password authenticatiom;
fLanguage
English
Publisher
ieee
Conference_Titel
Computer Software and Applications Conference (COMPSAC), 2010 IEEE 34th Annual
Conference_Location
Seoul
ISSN
0730-3157
Print_ISBN
978-1-4244-7512-4
Electronic_ISBN
0730-3157
Type
conf
DOI
10.1109/COMPSAC.2010.70
Filename
5676281
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