Pixel Value Graphical Password Scheme: Compatibility of K-means Clustering Algorithm as Pixel Value Password Fault Tolerance Mechanism

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

doi:doi:10.11648/j.ijsmit.20190502.13

Pixel Value Graphical Password Scheme: Compatibility of K-means Clustering Algorithm as Pixel Value Password Fault Tolerance Mechanism

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

Published in International Journal of Sustainability Management and Information Technologies (Volume 5, Issue 2)

Received: 13 December 2019 Published: 6 January 2020

Views: Downloads:

Download PDF

Share This Article

Twitter
Linked In
Facebook

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.

Published in	International Journal of Sustainability Management and Information Technologies (Volume 5, Issue 2)
DOI	10.11648/j.ijsmit.20190502.13
Page(s)	39-44
Creative Commons	This is an Open Access article, distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium or format, provided the original work is properly cited.
Copyright	Copyright © The Author(s), 2020. Published by Science Publishing Group

Keywords

PVAC, PassPix, K-means Algorithm, Graphical Password, Fault Tolerance, Euclidean Distance, Pixel Value, Image Query, Access Control

References

[1]	M. A. M. Shukran & M. S. F. M. Yunus, “Method and System For Authenticating User Using Graphical Password For Access Control,” Malaysian Patent MY-167835-A, 2018.
[2]	M. S. F. M. Yunus, "Dynamic Analysis of Pixel Value Graphical Password Scheme," Master Thesis, National Defense University of Malaysia, Kuala Lumpur, 2014.
[3]	M. A. M. Shukran, M. S. F. M. Yunus, M. N. Abdullah, M. N. Ismail & M. R. M. Isa, "Pixel Value Graphical Password: A PassPix Clustering Technique For Password Fault Tolerance," International Journal of Recent Technology and Engineering (IJRTE) ISSN: 2277-3878, Volume-8 Issue-3, September 2019, pp. 2973-2976.
[4]	L. Fei-Fei, R. Fergus & P. Perona, "Learning generative visual models from few training examples: an incremental Bayesian approach tested on 101 object categories", IEEE. CVPR 2004, Workshop on Generative-Model Based Vision. 2004.
[5]	M. Panda, A. E. Hassanien, & A. Abraham, "Hybrid Data mining approach for image segmentation based Classification," Biometrics: Concepts, Methodologies, Tools, and Applications, 2017, pp. 1543-1561.
[6]	B. A. Pimentel, & R. M. Souza, "Multivariate Fuzzy C-Means algorithms with weighting," Neurocomputing, 174, 2016, pp. 946-965.
[7]	E. Schubert, J. Sander, M. Ester, H. P. Kriegel & X. Xu, "DBSCAN Revisited, Revisited: Why and How You Should (Still) Use DBSCAN," ACM Trans. Database Syst. 42 (3): 19:1–19:21. doi: 10.1145/3068335, 2017, pp. 0362-5915.
[8]	A. Fahad, N. AlShatri, Z. Tari, A. Alamri, I. Khalil, A. Y. Zomaya & A. Bouras, "A Survey of Clustering Algorithms for Big Data: Taxonomy and Empirical Analysis," IEEE transactions on emerging topics in computing, 2 (3), 2014, pp. 267-279.
[9]	P. Sharma, & J. Suji, "A review on image segmentation with its clustering techniques," International Journal of Signal Processing, Image Processing and Pattern Recognition, 9 (5), 2016, pp. 209-218.
[10]	J. Macqueen, "Some methods for classification and analysis of multivariate observations," Proceedings of the fifth Berkeley symposium on mathematical statistics and probability, 1, 1967, pp. 281-297.
[11]	K. Rajalakshmi, D. S. Dhenakaran, & N. Roobin, "Comparative Analysis of K-Means Algorithm in Disease Prediction," International Journal of Science, Engineering and Technology Research (IJSETR), 4 (7), 2015, pp. 1-3.
[12]	W. Wang, Y. Jiong & M. Richard, "STING: A statistical information grid approach to spatial data mining," VLDB. Vol. 97, 1997.
[13]	WhatsApp Inc., WhatsApp Features, Available: https://www.whatsapp.com/features/, 2019.

Cite This Article

Plain Text BibTeX RIS

APA Style

Mohd Afizi Mohd Shukran, Mohd Sidek Fadhil Mohd Yunus, Muhammad Naim Abdullah, Mohd Nazri Ismail, Mohammad Adib Khairuddin, et al. (2020). 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, 5(2), 39-44. https://doi.org/10.11648/j.ijsmit.20190502.13

Copy | Download

ACS Style

Mohd Afizi Mohd Shukran; Mohd Sidek Fadhil Mohd Yunus; Muhammad Naim Abdullah; Mohd Nazri Ismail; Mohammad Adib Khairuddin, et al. Pixel Value Graphical Password Scheme: Compatibility of K-means Clustering Algorithm as Pixel Value Password Fault Tolerance Mechanism. Int. J. Sustain. Manag. Inf. Technol. 2020, 5(2), 39-44. doi: 10.11648/j.ijsmit.20190502.13

Copy | Download

AMA Style

Mohd Afizi Mohd Shukran, Mohd Sidek Fadhil Mohd Yunus, Muhammad Naim Abdullah, Mohd Nazri Ismail, Mohammad Adib Khairuddin, et al. Pixel Value Graphical Password Scheme: Compatibility of K-means Clustering Algorithm as Pixel Value Password Fault Tolerance Mechanism. Int J Sustain Manag Inf Technol. 2020;5(2):39-44. doi: 10.11648/j.ijsmit.20190502.13

Copy | Download

@article{10.11648/j.ijsmit.20190502.13,
  author = {Mohd Afizi Mohd Shukran and Mohd Sidek Fadhil Mohd Yunus and Muhammad Naim Abdullah and Mohd Nazri Ismail and Mohammad Adib Khairuddin and Kamaruzaman Maskat and Mohd Rizal Mohd Isa and Norshahriah Abdul Wahab and Mohd Fahmi Mohamad Amran},
  title = {Pixel Value Graphical Password Scheme: Compatibility of K-means Clustering Algorithm as Pixel Value Password Fault Tolerance Mechanism},
  journal = {International Journal of Sustainability Management and Information Technologies},
  volume = {5},
  number = {2},
  pages = {39-44},
  doi = {10.11648/j.ijsmit.20190502.13},
  url = {https://doi.org/10.11648/j.ijsmit.20190502.13},
  eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.ijsmit.20190502.13},
  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.},
 year = {2020}
}

Copy | Download

TY  - JOUR
T1  - Pixel Value Graphical Password Scheme: Compatibility of K-means Clustering Algorithm as Pixel Value Password Fault Tolerance Mechanism
AU  - Mohd Afizi Mohd Shukran
AU  - Mohd Sidek Fadhil Mohd Yunus
AU  - Muhammad Naim Abdullah
AU  - Mohd Nazri Ismail
AU  - Mohammad Adib Khairuddin
AU  - Kamaruzaman Maskat
AU  - Mohd Rizal Mohd Isa
AU  - Norshahriah Abdul Wahab
AU  - Mohd Fahmi Mohamad Amran
Y1  - 2020/01/06
PY  - 2020
N1  - https://doi.org/10.11648/j.ijsmit.20190502.13
DO  - 10.11648/j.ijsmit.20190502.13
T2  - International Journal of Sustainability Management and Information Technologies
JF  - International Journal of Sustainability Management and Information Technologies
JO  - International Journal of Sustainability Management and Information Technologies
SP  - 39
EP  - 44
PB  - Science Publishing Group
SN  - 2575-5110
UR  - https://doi.org/10.11648/j.ijsmit.20190502.13
AB  - 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.
VL  - 5
IS  - 2
ER  -

Copy | Download

Author Information

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

Download PDF

Sections

Plain Text BibTeX RIS

APA Style

Mohd Afizi Mohd Shukran, Mohd Sidek Fadhil Mohd Yunus, Muhammad Naim Abdullah, Mohd Nazri Ismail, Mohammad Adib Khairuddin, et al. (2020). 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, 5(2), 39-44. https://doi.org/10.11648/j.ijsmit.20190502.13

Copy | Download

ACS Style

Mohd Afizi Mohd Shukran; Mohd Sidek Fadhil Mohd Yunus; Muhammad Naim Abdullah; Mohd Nazri Ismail; Mohammad Adib Khairuddin, et al. Pixel Value Graphical Password Scheme: Compatibility of K-means Clustering Algorithm as Pixel Value Password Fault Tolerance Mechanism. Int. J. Sustain. Manag. Inf. Technol. 2020, 5(2), 39-44. doi: 10.11648/j.ijsmit.20190502.13

Copy | Download

AMA Style

Mohd Afizi Mohd Shukran, Mohd Sidek Fadhil Mohd Yunus, Muhammad Naim Abdullah, Mohd Nazri Ismail, Mohammad Adib Khairuddin, et al. Pixel Value Graphical Password Scheme: Compatibility of K-means Clustering Algorithm as Pixel Value Password Fault Tolerance Mechanism. Int J Sustain Manag Inf Technol. 2020;5(2):39-44. doi: 10.11648/j.ijsmit.20190502.13

Copy | Download

@article{10.11648/j.ijsmit.20190502.13,
  author = {Mohd Afizi Mohd Shukran and Mohd Sidek Fadhil Mohd Yunus and Muhammad Naim Abdullah and Mohd Nazri Ismail and Mohammad Adib Khairuddin and Kamaruzaman Maskat and Mohd Rizal Mohd Isa and Norshahriah Abdul Wahab and Mohd Fahmi Mohamad Amran},
  title = {Pixel Value Graphical Password Scheme: Compatibility of K-means Clustering Algorithm as Pixel Value Password Fault Tolerance Mechanism},
  journal = {International Journal of Sustainability Management and Information Technologies},
  volume = {5},
  number = {2},
  pages = {39-44},
  doi = {10.11648/j.ijsmit.20190502.13},
  url = {https://doi.org/10.11648/j.ijsmit.20190502.13},
  eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.ijsmit.20190502.13},
  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.},
 year = {2020}
}

Copy | Download

TY  - JOUR
T1  - Pixel Value Graphical Password Scheme: Compatibility of K-means Clustering Algorithm as Pixel Value Password Fault Tolerance Mechanism
AU  - Mohd Afizi Mohd Shukran
AU  - Mohd Sidek Fadhil Mohd Yunus
AU  - Muhammad Naim Abdullah
AU  - Mohd Nazri Ismail
AU  - Mohammad Adib Khairuddin
AU  - Kamaruzaman Maskat
AU  - Mohd Rizal Mohd Isa
AU  - Norshahriah Abdul Wahab
AU  - Mohd Fahmi Mohamad Amran
Y1  - 2020/01/06
PY  - 2020
N1  - https://doi.org/10.11648/j.ijsmit.20190502.13
DO  - 10.11648/j.ijsmit.20190502.13
T2  - International Journal of Sustainability Management and Information Technologies
JF  - International Journal of Sustainability Management and Information Technologies
JO  - International Journal of Sustainability Management and Information Technologies
SP  - 39
EP  - 44
PB  - Science Publishing Group
SN  - 2575-5110
UR  - https://doi.org/10.11648/j.ijsmit.20190502.13
AB  - 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.
VL  - 5
IS  - 2
ER  -

Copy | Download