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Data Security for Connected Governments and Organisations: Managing Automation and Artificial Intelligence

Data Security for Connected Governments and Organisations: Managing Automation and Artificial Intelligence

Heru Susanto, Leu Fang Yie, Didi Rosiyadi, Akbari Indra Basuki, Desi Setiana
Copyright: © 2022 |Pages: 23
ISBN13: 9781668436943|ISBN10: 1668436949|EISBN13: 9781668436950
DOI: 10.4018/978-1-6684-3694-3.ch011
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MLA

Susanto, Heru, et al. "Data Security for Connected Governments and Organisations: Managing Automation and Artificial Intelligence." Research Anthology on Cross-Disciplinary Designs and Applications of Automation, edited by Information Resources Management Association, IGI Global, 2022, pp. 191-213. https://doi.org/10.4018/978-1-6684-3694-3.ch011

APA

Susanto, H., Yie, L. F., Rosiyadi, D., Basuki, A. I., & Setiana, D. (2022). Data Security for Connected Governments and Organisations: Managing Automation and Artificial Intelligence. In I. Management Association (Ed.), Research Anthology on Cross-Disciplinary Designs and Applications of Automation (pp. 191-213). IGI Global. https://doi.org/10.4018/978-1-6684-3694-3.ch011

Chicago

Susanto, Heru, et al. "Data Security for Connected Governments and Organisations: Managing Automation and Artificial Intelligence." In Research Anthology on Cross-Disciplinary Designs and Applications of Automation, edited by Information Resources Management Association, 191-213. Hershey, PA: IGI Global, 2022. https://doi.org/10.4018/978-1-6684-3694-3.ch011

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Abstract

Digital ecosystems have grown rapidly over the years, and governments are investing in digital provision for their processes and services. Despite the advantages of distributed technologies, there are many security issues as well that result in breaches of data privacy with serious impact including legal and reputational implications. To deal with such threats, government agencies need to thoughtfully improve their security defences to protect data and systems by using automation and artificial intelligence (AI), as well as easing the data security measures including early warning of threats and detection. This study provides a comprehensive view of AI and automaton to highlight challenges and issues concerning data security and suggests steps to combat the issues. The authors demonstrate the role of AI-driven security tools and automation to mitigate the impact of data breaches to also propose recommendations for government agencies to enhance their data security protection.

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