Next Article in Journal
Neural Network Analysis for Microplastic Segmentation
Previous Article in Journal
Live-Cell Systems in Real-Time Biomonitoring of Water Pollution: Practical Considerations and Future Perspectives
Previous Article in Special Issue
Improving Ponzi Scheme Contract Detection Using Multi-Channel TextCNN and Transformer
Review

The Impact of Artificial Intelligence on Data System Security: A Literature Review

1
ISEC Lisboa, Instituto Superior de Educação e Ciências, 1750-142 Lisbon, Portugal
2
Research Unit on Governance, Competitiveness and Public Policies (GOVCOPP), University of Aveiro, 3810-193 Aveiro, Portugal
*
Author to whom correspondence should be addressed.
Academic Editor: Ernesto Damiani
Sensors 2021, 21(21), 7029; https://doi.org/10.3390/s21217029
Received: 31 July 2021 / Revised: 29 September 2021 / Accepted: 21 October 2021 / Published: 23 October 2021
(This article belongs to the Special Issue Blockchain for IoT Security, Privacy and Intelligence)
Diverse forms of artificial intelligence (AI) are at the forefront of triggering digital security innovations based on the threats that are arising in this post-COVID world. On the one hand, companies are experiencing difficulty in dealing with security challenges with regard to a variety of issues ranging from system openness, decision making, quality control, and web domain, to mention a few. On the other hand, in the last decade, research has focused on security capabilities based on tools such as platform complacency, intelligent trees, modeling methods, and outage management systems in an effort to understand the interplay between AI and those issues. the dependence on the emergence of AI in running industries and shaping the education, transports, and health sectors is now well known in the literature. AI is increasingly employed in managing data security across economic sectors. Thus, a literature review of AI and system security within the current digital society is opportune. This paper aims at identifying research trends in the field through a systematic bibliometric literature review (LRSB) of research on AI and system security. the review entails 77 articles published in the Scopus® database, presenting up-to-date knowledge on the topic. the LRSB results were synthesized across current research subthemes. Findings are presented. the originality of the paper relies on its LRSB method, together with an extant review of articles that have not been categorized so far. Implications for future research are suggested. View Full-Text
Keywords: artificial intelligence; security; security of data; security systems artificial intelligence; security; security of data; security systems
Show Figures

Figure 1

MDPI and ACS Style

Raimundo, R.; Rosário, A. The Impact of Artificial Intelligence on Data System Security: A Literature Review. Sensors 2021, 21, 7029. https://doi.org/10.3390/s21217029

AMA Style

Raimundo R, Rosário A. The Impact of Artificial Intelligence on Data System Security: A Literature Review. Sensors. 2021; 21(21):7029. https://doi.org/10.3390/s21217029

Chicago/Turabian Style

Raimundo, Ricardo, and Albérico Rosário. 2021. "The Impact of Artificial Intelligence on Data System Security: A Literature Review" Sensors 21, no. 21: 7029. https://doi.org/10.3390/s21217029

Find Other Styles
Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. See further details here.

Article Access Map by Country/Region

1
Back to TopTop