Issue |
MATEC Web Conf.
Volume 139, 2017
2017 3rd International Conference on Mechanical, Electronic and Information Technology Engineering (ICMITE 2017)
|
|
---|---|---|
Article Number | 00205 | |
Number of page(s) | 7 | |
DOI | https://doi.org/10.1051/matecconf/201713900205 | |
Published online | 05 December 2017 |
Exploring Topsnut-Graphical Passwords by Twin Odd-elegant Trees
1 School of Electronics Engineering and Computer Science, Peking University, 100871, China
2 College of Mathematics and Statistics, Northwest Normal University, Lanzhou, 730070, China
3 College of Electronic and Information Engineering, Lanzhou Jiaotong University, Lanzhou 730070, China
* e-mail: jxu@pku.edu.cn
Graphical passwords are facing a good opportunity as 2-dimension codes are accepted by many people, since it has been applied in mobile devices, electronic equipments with touch screen, and so on. QR codes can be considered as a type of graphical passwords. Topsnut-graphical password differs from the existing graphical passwords, and has been investigated and developed. In this article, a new type of Topsnut-graphical passwords has been designed by technique of graph theory, called twin odd-elegant labelling. We make the twin odd-elegant graphs for one-key vs two or more locks (conversely, one-lock vs two or more keys). These Topsnut-GPWs show perfect matching characteristics of locks (TOE-lock-models) and keys (TOE-key-models). We show examples for testing our methods which can be easily transformed into effective algorithms.
© The Authors, published by EDP Sciences, 2017
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (http://creativecommons.org/licenses/by/4.0/).
Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.
Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.
Initial download of the metrics may take a while.