Demystifying Artificial Intelligence in Cybersecurity: From Theory to Practice

During the seminar, we will address the following questions: what artificial intelligence is (and what it is not), why its branch of computational intelligence is particularly important, and what its synergy with cybersecurity looks like. Computational intelligence, supported by computing power, enables us to solve complex problems that traditional approaches cannot handle.

Participants will gain an understanding of the basic concepts, modern practical approaches, and use cases of technologies that are accessible even to micro-enterprises. Among other things, we will use free tools to demonstrate a practical example of data mining, which can be applied to detect anomalies and threats in network data.

Special emphasis will be placed on key security systems, such as Intrusion Detection Systems (IDS), Intrusion Prevention Systems (IPS), Security Information and Event Management (SIEM), and Honeypot detection systems for identifying attackers. These approaches will be presented as practical examples of how companies can enhance their resilience to cyber threats. We will also review key developments in Slovenia and the EU, along with the latest legislation in the field of cybersecurity (ZInfV-1 and the NIS-2 directive), which introduces stricter requirements for managing cyber risks, and we will show how companies can prepare in time.

Key objectives of the seminar:

• Understanding the basics: What artificial intelligence is, what computational intelligence is, and their roles in cybersecurity.
• Practical demonstration: Showcasing the use of free tools in cybersecurity.
• Company preparedness: Reviewing the key requirements of ZInfV-1 and NIS-2 and outlining steps for timely preparation.

The lecture will be delivered by Dr. Damijan Novak, Assistant Professor at the Faculty of Electrical Engineering and Computer Science, University of Maribor. He has been conducting research in artificial intelligence since 2011, focusing primarily on machine learning and reinforcement learning algorithms, in which he also earned his PhD. His research interests include data mining, intelligent agents, and related methods such as computational intelligence, applied across various domains, including cybersecurity. He places special emphasis on the development of simulators for generating synthetic data for training and testing intelligent systems. His work combines theory with advanced approaches and involves participation in interdisciplinary projects both in Slovenia and abroad.