The Utility of AI in the Management of Cybersecurity
Gouri Sankar Nayak, Jitendra Kumar Chaudhary, Manvendra Kumar Singh, D. Ganesh, G. Suni, Abdullah Samdani · 2024
The extensive use of technology in today’s world is strongly correlated with the rise in risks related to cybersecurity. It is essential to focus on cybersecurity management given how organisations are changing today. To solve these problems, machine learning (ML) methods and an understanding of artificial intelligence (AI) might be employed. Nevertheless, a learning-oriented cybersecurity algorithm’s efficacy may differ according to the cybersecurity elements and the data properties. This study reports the results of a scientific assessment of several categorisation methods, including linear discriminant analysis (LDA), k-nearest neighbours (KNN), random forest (RF) and convolution neural network (CNN). WUSTL-IIoT-2012 databases have been utilised for evaluating the proposed approaches. The research outcomes demonstrate the suitability of the suggested ML and deep learning-oriented method for managing cybersecurity, accomplishing substantial detection accuracy and supplying the potential to manage freshly arising cyber risks.