Artículo

Neural Networks Toward Cybersecurity: Domain Map Analysis of State-of-the-Art Challenges

Resumen

The growing interest in applying neural networks for cybersecurity has prompted a substantial increase in related research. This paper presents a comprehensive bibliometric analysis of research on cybersecurity towards neural networks published in the Web of Science over the past two decades (2003–2023) using bibliometric methods and CiteSpace software. The analysis encompasses yearly publication trends, types of publications, and trends across various dimensions such as publishing sources, organizations, researchers, countries, and keywords. Additionally, timeline and burst detection analyses were conducted to identify significant topic trends and citations in the last two decades. It also outlines the latest trends, under-explored topics, and open challenges.
Farias, Miriam Leite (57220120696); Alcoforado, Daniela Gomes (57219166657); Patriota, Verônyca Kezya Santos Sousa (57226809061); Palha, Armando Perez (57226815268); de Souza-Leão, André Luiz Maranhão (55337966500)
Qualitative research in marketing: Overview of the Brazilian scientific production from 2010 to 2019
2021
10.5585/REMARK.V20I3.16603
https://www.scopus.com/inward/record.uri?eid=2-s2.0-85112740906&doi=10.5585%2fREMARK.V20I3.16603&partnerID=40&md5=73a94c0f1af4b927cbabea86a79be751
All Open Access; Gold Open Access
Scopus
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