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.
Shevchuk, Ruslan (24178081800); Martsenyuk, Vasyl (6603347161)
Neural Networks Toward Cybersecurity: Domaine Map Analysis of State-of-the-Art Challenges
2024
10.1109/ACCESS.2024.3411632
https://www.scopus.com/inward/record.uri?eid=2-s2.0-85196117289&doi=10.1109%2fACCESS.2024.3411632&partnerID=40&md5=357fba1bb9ac6d7a07fd5790a602c027
University of Bielsko-Biala, Department of Computer Science and Automatics, Bielsko-Biała, 43-309, Poland; West Ukrainian National University, Department of Computer Science, Ternopil, 46009, Ukraine
All Open Access; Gold Open Access
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