Goal:
The aim of the course is to provide students with a comprehensive understanding of the fundamental methods of artificial intelligence and machine learning, as well as their applications in the field of cybersecurity. Students will gain insight into modern AI-based cybersecurity solutions, with particular emphasis on anomaly detection, malware analysis, support for red teaming activities, and the security aspects of generative artificial intelligence and Large Language Models (LLMs). Furthermore, the course aims to develop practical skills in the application, evaluation, and security-oriented analysis of artificial intelligence methods and techniques.
Course description:
The course provides an overview of the fundamental concepts of artificial intelligence, machine learning, and neural networks, and introduces their applications in various areas of cybersecurity. Students will become familiar with classical machine learning algorithms and their use in tasks such as anomaly detection and malware detection. The course places particular emphasis on cybersecurity applications of reinforcement learning, AI-based red teaming solutions, the operation of generative artificial intelligence and Large Language Models (LLMs), as well as attacks against and defenses for these technologies. Furthermore, the course examines the role of Explainable Artificial Intelligence (XAI) in security decision support and in improving the transparency, trustworthiness, and reliability of AI systems. The course also includes project-based practical components, during which students apply the acquired methods and techniques to real-world cybersecurity problems.