Elisa, Noe, Yang, Longzhi, Chao, Fei, Naik, Nitin and Boongoen, Tossapon (2023). A Secure and Privacy-Preserving E-Government Framework using Blockchain and Artificial Immunity. IEEE Access, 11 , pp. 8773-8789.
Abstract
Electronic Government (e-Government) systems constantly provide greater services to people, businesses, organisations, and societies by offering more information, opportunities, and platforms with the support of advances in information and communications technologies. This usually results in increased system complexity and sensitivity, necessitating stricter security and privacy-protection measures. The majority of the existing e-Government systems are centralised, making them vulnerable to privacy and security threats, in addition to suffering from a single point of failure. This study proposes a decentralised e-Government framework with integrated threat detection features to address the aforementioned challenges. In particular, the privacy and security of the proposed e-Government system are realised by the encryption, validation, and immutable mechanisms provided by Blockchain. The insider and external threats associated with blockchain transactions are minimised by the employment of an artificial immune system, which effectively protects the integrity of the Blockchain. The proposed e-Government system was validated and evaluated by using the framework of Ethereum Visualisations of Interactive, Blockchain, Extended Simulations (i.e. eVIBES simulator) with two publicly available datasets. The experimental results show the efficacy of the proposed framework in that it can mitigate insider and external threats in e-Government systems whilst simultaneously preserving the privacy of information.
Publication DOI: | https://doi.org/10.1109/ACCESS.2023.3239814 |
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Divisions: | College of Engineering & Physical Sciences College of Engineering & Physical Sciences > School of Computer Science and Digital Technologies > Software Engineering & Cybersecurity College of Engineering & Physical Sciences > School of Computer Science and Digital Technologies Aston University (General) |
Additional Information: | This work is licensed under a Creative Commons Attribution 4.0 License. For more information, see https://creativecommons.org/licenses/by/4.0/. Funding: This work was supported in part by the Commonwealth Scholarship Commission under Grant CSC-TZCS-2017-717, and in part by the Royal Academy of Engineering Industry Academia Partnership Programme under Grant IAPP1\100077. |
Uncontrolled Keywords: | Artificial immune systems,Artificial intelligence,Blockchains,Business,E-Government,Electronic government,Peer-to-peer computing,Privacy,artificial immune system,blockchain,insider threat,privacy-preserving,General Computer Science,General Materials Science,General Engineering,Electrical and Electronic Engineering |
Publication ISSN: | 2169-3536 |
Last Modified: | 02 Dec 2024 08:49 |
Date Deposited: | 07 Feb 2023 08:25 |
Full Text Link: | |
Related URLs: |
https://ieeexpl ... cument/10025716
(Publisher URL) http://www.scop ... tnerID=8YFLogxK (Scopus URL) |
PURE Output Type: | Article |
Published Date: | 2023-01-30 |
Published Online Date: | 2023-01-25 |
Accepted Date: | 2023-01-12 |
Authors: |
Elisa, Noe
Yang, Longzhi Chao, Fei Naik, Nitin ( 0000-0002-0659-9646) Boongoen, Tossapon |