Cyber threats and network attacks are becoming more sophisticated each day. The number of daily attacks globally is rising, and the ways and techniques used to infiltrate company systems and personal devices are diverse. Behind the attacks are lone attackers, organized groups, and entire governments. The recourses for carrying out attacks are increasing, and today cyber attacks can have severe, widespread effects and consequences. These factors combine to create problems for security teams to keep up with the pace, and smarter solutions are required.

This thesis gives an overview of how artificial intelligence (AI) approaches, and sub-domains such as machine learning and deep learning, can be applied to cybersecurity issues. This thesis also aims to showcase existing AI technologies and how they improve cyber security. With AI security systems can become more predictive and proactive in detection and response, as well as save time in manual repetitive security tasks. In this thesis, employees at If insurance company who work with network monitoring and network security were interviewed. The purpose of the interviews was to find out what sort of problems they have encountered in their tasks. Additionally, possible AI-based solutions for the defined problems are represented in this thesis.