Security impacts of artificial intelligence on cybersecurity

In recent years, there has been a huge increase in the quality of the output of neural networks generating synthetic content, which has gone hand in hand with a significant simplification of the use of AI-based tools and their increased availability. Thus, the growing trend in the use of artificial intelligence brings new challenges to the field of cybersecurity. The most prominent examples are the use of "deepfakes" to attack biometric systems or the use of deep learning techniques to detect cyber attacks. The goal of this work is to analyze new trends, approaches, real attacks, their characteristics, impacts, and potential applications in a selected area of cybersecurity. The work should then propose new AI-based protection methods based on the analysis and research on the state of security for the selected areas.

Recommended areas of focus for the thesis:
Impact of generative AI on code and application security
The human factor in AI-based attacks - e.g., increasing the ability of humans to recognize these types of attacks
Impacts of generative AI on the security of biometric authentication (voice, face, ...)

Participation in relevant international conferences and publication in scientific journals are expected.

Co-supervised by Dr. Kamil Malinka.