The thesis examines the potential of using artificial intelligence (AI) to enhance cybersecurity within the European Union (EU). In the context of increasing cyber threats and the sophistication of cyberattacks, the thesis analyses how AI contributes to threat detection, the establishment of security standards, and the preservation of the EU's digital sovereignty. The aim of the research is to explore the possibilities of automating intrusion detection and proactive threat response using AI, ensuring compliance with existing legal and political frameworks that regulate this domain. The methodology includes a review of existing literature, analysis of legislative initiatives, and a study of AI tools for cybersecurity. Qualitative methods were employed, and the research findings indicate that machine learning and deep learning techniques effectively detect anomaly patterns in network traffic, enabling swift identification and response to cyberattacks. It also highlights the need to upgrade existing security standards and adapt regulatory guidelines to protect digital assets in the EU.
The thesis significantly contributes to the field of cybersecurity by offering strategic directions for integrating AI into security protocols. Practical benefits include improved protection of data and infrastructure, which is crucial for the public sector and industry. The societal impact of the research is reflected in enhanced digital security and public trust in digital services. The thesis provides a foundation for further research on the application of AI in cybersecurity and encourages the development of advanced security solutions and policies.
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