This course provides a comprehensive introduction to the key concepts, methods, and challenges in modern data security. Students gain an up-to-date understanding of the theoretical foundations and technological developments that shape the protection of digital information across scientific and industrial domains. The course equips participants with both analytical and practical skills needed to conceptualize data security challenges, develop and maintain security solutions and environments, and evaluate their business relevance and innovative potential.

The second part of the course focuses on novel challenges in applied artificial intelligence (AI) security. We cover input data manipulation, different poisoning techniques, as well as different confidentiality attacks in AI systems e.g., membership inference and model inversion. We conclude the course with AI forensics i.e., the specific techniques required to analyse AI failures or the use of AI by criminals.

Major topics:
The students will be equipped with relevant knowledge in the following domains which they will be able to utilize in future applied data science tasks:

• Physical security and social engineering;
• Data encryption;
• Data security and privacy;
• Input data manipulation attacks against AI;
• Confidentiality attacks against AI;
• Integrity and availability attacks against AI;
• AI forensics;