UUM Electronic Theses and Dissertation
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Towards an effective recognition graphical password mechanism based on cultural familiarity

Shaban, Abdullah Ibrahim (2017) Towards an effective recognition graphical password mechanism based on cultural familiarity. Masters thesis, Universiti Utara Malaysia.

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Text-based passwords for authentication are exposed to the dictionary attack as users tend to create weak passwords for easy memorability. When dealing with user’s authentication, pictures are more likely to be simply remembered in comparison with words. Hence, this study aimed to determine the types of pictures in accordance to users’ cultural background. It also investigated the relationship between the choices of password and the cultural familiarity along with the effect of Graphical Password (GP) on security and usability. A list of guidelines was proposed for the recognition of graphical passwords. This is believed to increase the security as well as usability. A total of 40 students were recruited to build a GP database. Further, an evaluation was conducted to investigate users’ familiarity and recognition of the GP from the database using 30 other respondents. The results showed that the 30 participants positively responded to the familiar pictures in accordance to their cultures. The result of successful login rate was 79.51% which indicates that cultural-based GP has increased the respondents’ familiarity by promoting their memorability. Further, the respondents who chose familiar GP had higher guessing attack rate than the unfamiliar GP. Finally, a total of 8 guidelines were established based on the aspects that correspond to the users’ preferences for choosing and processing GP. These guidelines can be used by graphical password system designers to develop effective GP systems

Item Type: Thesis (Masters)
Supervisor : Zakaria, Nur Haryani
Item ID: 6558
Uncontrolled Keywords: System authentication, Graphical password, Security attack, Usability, Cultural background
Subjects: T Technology > T Technology (General) > T58.5-58.64 Information technology
Divisions: Awang Had Salleh Graduate School of Arts & Sciences
Date Deposited: 21 Nov 2017 01:22
Last Modified: 18 Aug 2021 06:54
Department: Awang Had Salleh Graduate School of Arts and Sciences
Name: Zakaria, Nur Haryani
URI: https://etd.uum.edu.my/id/eprint/6558

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