Volume 5, Issue 2, December 2019, Page: 39-44
Pixel Value Graphical Password Scheme: Compatibility of K-means Clustering Algorithm as Pixel Value Password Fault Tolerance Mechanism
Mohd Afizi Mohd Shukran, Department of Computer Science, National Defense University of Malaysia, Kuala Lumpur, Malaysia
Mohd Sidek Fadhil Mohd Yunus, Department of Computer Science, National Defense University of Malaysia, Kuala Lumpur, Malaysia
Muhammad Naim Abdullah, Department of Computer Science, National Defense University of Malaysia, Kuala Lumpur, Malaysia
Mohd Nazri Ismail, Department of Computer Science, National Defense University of Malaysia, Kuala Lumpur, Malaysia
Mohammad Adib Khairuddin, Department of Computer Science, National Defense University of Malaysia, Kuala Lumpur, Malaysia
Kamaruzaman Maskat, Department of Computer Science, National Defense University of Malaysia, Kuala Lumpur, Malaysia
Mohd Rizal Mohd Isa, Department of Computer Science, National Defense University of Malaysia, Kuala Lumpur, Malaysia
Norshahriah Abdul Wahab, Department of Computer Science, National Defense University of Malaysia, Kuala Lumpur, Malaysia
Mohd Fahmi Mohamad Amran, Department of Computer Science, National Defense University of Malaysia, Kuala Lumpur, Malaysia
Received: Dec. 13, 2019;       Published: Jan. 6, 2020
DOI: 10.11648/j.ijsmit.20190502.13      View  481      Downloads  110
Abstract
In September 2018, the patent for pixel value graphical password scheme was granted in Malaysia. The graphical password scheme was designed to reduce the complexity of previously developed graphical password scheme where a user only requires to load their personal image as password instead of complex graphical challenge during authentication. As the guardian of digital access, Pixel Value Access Control was highly invincible from password pixel forgery attack where a little bit different pixel value derived from loaded image will deny the access. Only the original enrolled image from a registered user can be recognized by Pixel Value Access Control to authenticate the respective username. That fact makes the graphical password scheme is a trusted access control mechanism but, on the other hand, it makes users bound with the only original password pixel image file. Thus, Pixel Value Access Control need to be installed the pixel value fault tolerance mechanism where it could allow users to acquire their password pixel image file from various storage media. The clustering technique was suggested to solve this issue where it allows an altered pixel password being recognized as the same group of the original pixel password. There are number of clustering algorithms developed for various purposed and application of digital image clustering. K-Means algorithm is one the partition-based clustering algorithm that found to be the simplest and fastest clustering algorithm as suggested by many researchers. This paper is mainly to exhibit the selection of K-Means clustering algorithm became the crucial algorithm for Pixel Value Access Control password pixel fault tolerance algorithm. Background of this topic was briefly explained in introduction section, the implementation of K-Means algorithm as Pixel Value Access Control fault tolerance was elaborate in section 2 and followed by validation of the implementation in section 3. At the end of this paper, there is conclusion for this study and followed by list of references.
Keywords
PVAC, PassPix, K-means Algorithm, Graphical Password, Fault Tolerance, Euclidean Distance, Pixel Value, Image Query, Access Control
To cite this article
Mohd Afizi Mohd Shukran, Mohd Sidek Fadhil Mohd Yunus, Muhammad Naim Abdullah, Mohd Nazri Ismail, Mohammad Adib Khairuddin, Kamaruzaman Maskat, Mohd Rizal Mohd Isa, Norshahriah Abdul Wahab, Mohd Fahmi Mohamad Amran, Pixel Value Graphical Password Scheme: Compatibility of K-means Clustering Algorithm as Pixel Value Password Fault Tolerance Mechanism, International Journal of Sustainability Management and Information Technologies. Vol. 5, No. 2, 2019, pp. 39-44. doi: 10.11648/j.ijsmit.20190502.13
Copyright
Copyright © 2019 Authors retain the copyright of this article.
This article is an open access article distributed under the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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