Strengthening cyber resilience in universities using artificial intelligence for proactive threat detection

Abstract

The data used by companies for decision making are exposed to various risks that can compromise their security. In this context, it is essential to identify tools to detect and manage these risks. Therefore, the main objective of this research was to conduct a bibliometric analysis aimed at assessing the development of scientific literature on the application of cyber resilience in universities using artificial intelligence for proactive threat detection. To achieve this purpose, the Scimago portal, specialized in the analysis of scientific production, was used. The study reviewed the distribution of quartiles using bibliometric indicators such as the H-index, journal impact factor, number of published documents, average citations per document, international scientific collaboration, and citations from public funding entities. Likewise, the number of articles cited in the most relevant journals of each quartile was evaluated in order to assess the importance of scientific innovation in improving proactive threat detection through cyber resilience. The results show that most of the scientific production is concentrated in journals belonging to countries with high technological development, especially in the areas of threat detection and application of artificial intelligence. However, there is a low diffusion of research related to cyber resilience in universities through artificial intelligence. which suggests the need to increase investment in science and technology, considering the high risk of cybersecurity attacks to which these institutions are exposed.