Early detection and mitigation of cyber attacks with machine learning and artificial intelligence
En-Cheng Liu · Applied and Computational Engineering · 2024
This research article explores the influence of leveraging machine learning algorithms (ML) and artificial intelligence (AI) in the early detection and mitigation of cyber attacks. With the rise of cybercriminal activities, traditional cybersecurity measures have proven inadequate. This study reviews the various AI and ML techniques, such as anomaly and cyber intelligence, which can be used in detecting cyberattacks before they occur. A case study on IBM security illustrates the practical implications and outcome of implementing machine learning and artificial intelligence in cybersecurity.