Towards an Architecture-based Ensemble Methods for Online Social Network Sensitive Data Privacy Protection

Authors

  • Felix Olutokunbo Idepefo Obafemi Awolowo University, Ile-Ife, Osun State, Nigeria
  • Bernard Ijesunor Akhigbe Obafemi Awolowo University, Ile-Ife, Osun State, Nigeria
  • Ojo Stephen Aderibigbe Lagos State Polytechnic, Ikorodu, Lagos, Lagos State, Nigeria
  • Babajide Samuel Afolabi Obafemi Awolowo University, Ile-Ife, Osun State, Nigeria

DOI:

https://doi.org/10.3991/ijes.v9i1.20819

Keywords:

Sensitive data protection model, Online social network, Blockchain technology, Cryptography, Consensus mechanism

Abstract


Abstract - In 2014, the world woke up to a giant data breach that leveraged users’ personal information that was taken from one of the world’s biggest social network platform. Based on the literature, this was possible because of the Centralised Architectural-based Approach to protecting the privacy of users’ online data. Although the literature is inundated with decentralized approaches, there is none to the best of our knowledge that uses an ensemble of methods and draws on a consensus mechanism to address the challenges caused by the Centralised Architectural-based Approach. This paper presents a decentralized approach that adopts and adapts an ensemble of methods. These methods include cryptographic, hashing, and the plenum byzantine fault tolerance algorithms that present a consensus platform, protocol, and mechanism to use the technology of blockchain in a novel manner as a significant contribution. This paper adopts the descriptive approach in its presentation as the usable implementation of the presented proposal is near completion with issues of computational overhead addressed based on preliminary results that show promise of being able to support agreement up to ≈ 75% in terms of making changes by participants in the chain.

Author Biographies

Felix Olutokunbo Idepefo, Obafemi Awolowo University, Ile-Ife, Osun State, Nigeria

Post Graduate Student, Department of Computer Science and Engineering, Obafemi Awolowo University, Ile-Ife, Osun State, Nigeria

Bernard Ijesunor Akhigbe, Obafemi Awolowo University, Ile-Ife, Osun State, Nigeria

Bernard Ijesunor Akhigbe holds a Ph.D. in computer science and he is a Senior Lecturer in the Department of Computer Science and Engineering, Obafemi Awolowo University, Nigeria. He researches generally in Information system and Software engineering with an interest in IoT and Blockchain for management gains. He has published widely and attended learned workshops and conferences both locally and internationally. He is a member of ISRG, ISKO France, NCS and CPN.

Ojo Stephen Aderibigbe, Lagos State Polytechnic, Ikorodu, Lagos, Lagos State, Nigeria

Ojo Stephen Aderibigbe holds a Ph.D in Computer Science and He is a Senior Lecturer in the Computer Science Department of the Lagos State Polytechnic, Ikorodu, Lagos State, Nigeria. He is a member NCS, CPN, and ISKO. His research focus on Information storage and Retrieval, and Collaborative Trust-Aware models. He has presented papers at both local and international conferences.

Babajide Samuel Afolabi, Obafemi Awolowo University, Ile-Ife, Osun State, Nigeria

Babajide Samuel Afolabi is a Professor in the Department of Computer Science and Engineering, Obafemi Awolowo University, Nigeria, who holds a Ph.D. from Université Nancy 2, Nancy, France. He is focused on developing applications for enhanced Living. He is currently the Director of the Obafemi Awolowo University Computer Centre. He researches in Information system and Software engineering. He is well-published and has attended learned conferences both locally and internationally. He is a member of ISRG, ISKO France, NCS, and CPN.

 

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Published

2021-03-23

How to Cite

Idepefo, F. O., Akhigbe, B. I., Aderibigbe, O. S., & Afolabi, B. S. (2021). Towards an Architecture-based Ensemble Methods for Online Social Network Sensitive Data Privacy Protection. International Journal of Recent Contributions from Engineering, Science & IT (iJES), 9(1), pp. 33–49. https://doi.org/10.3991/ijes.v9i1.20819

Issue

Vol. 9 No. 1 (2021)

Section

Papers

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