Cybersecurity challenges and opportunities of machine learning-based artificial intelligence
Authors: Czaja, P., Gdowski, B., Niemiec, M., Mees, W., Stoianov, N., Votis, K., Kharchenko, V., Katos, V. and Merialdo, M.
Journal: Neural Computing and Applications
Volume: 37
Issue: 33
Pages: 27931-27956
eISSN: 1433-3058
ISSN: 0941-0643
DOI: 10.1007/s00521-025-11604-9
Abstract:Artificial intelligence, machine learning, and cybersecurity are the topics of discussion of contemporary information technology sector and computing research. This study investigates the integration of machine learning-based artificial intelligence in the context of cybersecurity. This paper presents an overview of the recent literature, focusing on selected popular areas related to the challenges and opportunities that such implementations introduce. The authors also assess how selected problems related to the application of machine learning algorithms affect the real effectiveness represented by the resulting models. To support this analysis, an experimental study was conducted using a real-world cybersecurity system. This demonstration illustrates the practical implementation of a machine learning-based software solution in cybersecurity and highlights the potential challenges encountered during such implementations.
Source: Scopus