The Impact of Artificial Intelligence on Data System Security: A Literature Review.
artificial intelligence
security
security of data
security systems
Journal
Sensors (Basel, Switzerland)
ISSN: 1424-8220
Titre abrégé: Sensors (Basel)
Pays: Switzerland
ID NLM: 101204366
Informations de publication
Date de publication:
23 Oct 2021
23 Oct 2021
Historique:
received:
31
07
2021
revised:
29
09
2021
accepted:
21
10
2021
entrez:
13
11
2021
pubmed:
14
11
2021
medline:
17
11
2021
Statut:
epublish
Résumé
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
Identifiants
pubmed: 34770336
pii: s21217029
doi: 10.3390/s21217029
pmc: PMC8586986
pii:
doi:
Types de publication
Journal Article
Review
Langues
eng
Sous-ensembles de citation
IM
Références
Sensors (Basel). 2020 Apr 27;20(9):
pubmed: 32349242
Eur J Investig Health Psychol Educ. 2021 Mar 16;11(1):276-293
pubmed: 34542464