Journal article
PassPoints: Design and longitudinal evaluation of a graphical password system
International journal of human-computer studies, v 63(1), pp 102-127
2005
Abstract
Computer security depends largely on passwords to authenticate human users. However, users have difficulty remembering passwords over time if they choose a secure password, i.e. a password that is long and random. Therefore, they tend to choose short and insecure passwords. Graphical passwords, which consist of clicking on images rather than typing alphanumeric strings, may help to overcome the problem of creating secure and memorable passwords. In this paper we describe PassPoints, a new and more secure graphical password system. We report an empirical study comparing the use of PassPoints to alphanumeric passwords. Participants created and practiced either an alphanumeric or graphical password. The participants subsequently carried out three longitudinal trials to input their password over the course of 6 weeks. The results show that the graphical password users created a valid password with fewer difficulties than the alphanumeric users. However, the graphical users took longer and made more invalid password inputs than the alphanumeric users while practicing their passwords. In the longitudinal trials the two groups performed similarly on memory of their password, but the graphical group took more time to input a password.
Metrics
Details
- Title
- PassPoints: Design and longitudinal evaluation of a graphical password system
- Creators
- Susan Wiedenbeck - Drexel UniversityJim Waters - Drexel UniversityJean-Camille Birget - Rutgers, The State University of New JerseyAlex Brodskiy - Dept. of Computer Science, Polytechnic University, Brooklyn, NYNasir Memon - Dept. of Computer Science, Polytechnic University, Brooklyn, NY
- Publication Details
- International journal of human-computer studies, v 63(1), pp 102-127
- Publisher
- Elsevier
- Resource Type
- Journal article
- Language
- English
- Academic Unit
- [Retired Faculty]
- Web of Science ID
- WOS:000230237500006
- Scopus ID
- 2-s2.0-19944381937
- Other Identifier
- 991019167535204721
InCites Highlights
Data related to this publication, from InCites Benchmarking & Analytics tool:
- Collaboration types
- Domestic collaboration
- Web of Science research areas
- Computer Science, Cybernetics
- Ergonomics
- Psychology, Multidisciplinary