Description

Theory
1

Theory/Practice
1

Instructors

Isabel Praça

Contents

1 - Data Protection
1.1 - Data Acquisition, Storage, Access, Processing and Control
1.2 - Personal and Sensitive Data
1.3 - Data Rectification and Deletion
1.4 - Codes of Conduct and Certification
1.5 - Data Protection Officer
2 - Data Protection Regulations
2.1 - General Data Protection Regulation
2.2 - European Union Data Protection Regulation
3 - Privacy and Data Protection in Artificial Intelligence and Data Science Systems
4 - Information and Communication Technologies and Security Threats
5 - Types of Cybercrime
5.1 ? Malware
5.2 ? Phishing
5.3 ? Identity Theft
5.4 ? Cyberterrorism
5.5 ? Cybercrime Techniques
6 ? Cybercrime Prevention and Protection
7 ? Cybersecurity in Artificial Intelligence Systems
8 ? Artificial Intelligence applied to Cybersecurity
9 ? Artificial Intelligence Security

Learning Outcomes

CO1 - Master the main aspects to consider in Privacy and Security
CO2 - Understand how Privacy and Security should be considered and applied to Intelligent Systems
CO3 - Know and master the methods and techniques of Artificial Intelligence that can be applied to Privacy and Security
CO4 - Have a critical sense about the types of attacks on Artificial Intelligence and the methods and techniques to prevent, detect and mitigate them