Privacy by Design
7.5 ECTS creditsThe following components are included:
- Fundamental concepts of architectural tactics and patterns
- Privacy protection as quality attribute of software systems
- Introduction to privacy patterns, privacy anti-patterns, and privacy dark patterns
- Applying privacy patterns in agile development
- The relationship between artificial intelligence and data protection
The course comprises five modules.
Module 1 Introduction to privacy and the GDPR, 1.5 ECTS cr
The module includes the definitions, history and foundations of privacy with an emphasis on the challenges in information and communication technology. The focus is on the European and national (Swedish) laws regulating privacy, data protection and cyber safety, including agreements on transferring personal information beyond the EU. Some important decisions of the EU court in this area are discussed.
Module 2 Privacy enhancing technologies, 1.5 ECTS cr
The module introduces security and privacy mechanisms and technologies and proceeds to focus on how security and privacy mechanisms can be used to solve practical and theoretical problems, along with discussions of their advantages and disadvantages.
Module 3 Designing for privacy, 1.5 ECTS cr
The module introduces the foundations of privacy, data protection, and privacy enhancing technologies, and focuses on the concepts of privacy by design and privacy impact assessments by exploring the relevant background, their relationship to the foundation and fundamental human rights, and by introducing relevant methods.
Module 4 Privacy patterns for software design, 1.5 ECTS cr
The module deals with privacy aspects as part of software development. It particularly focuses on architectural tactics and patterns as reusable conceptual solutions to recurring problems in privacy protection. It also outlines how to use these concepts in agile development settings in order to engineer privacy into software.
Module 5 Artificial intelligence and data protection, 1.5 ECTS cr
This module focuses on the relationship between artificial intelligence and data protection, provides insight into the basics of artificial intelligence, and treats how to protect personal data when using various types of machine learning models. New legal obligations in European regulations concerning applications of AI and data protection are also discussed.
- Fundamental concepts of architectural tactics and patterns
- Privacy protection as quality attribute of software systems
- Introduction to privacy patterns, privacy anti-patterns, and privacy dark patterns
- Applying privacy patterns in agile development
- The relationship between artificial intelligence and data protection
The course comprises five modules.
Module 1 Introduction to privacy and the GDPR, 1.5 ECTS cr
The module includes the definitions, history and foundations of privacy with an emphasis on the challenges in information and communication technology. The focus is on the European and national (Swedish) laws regulating privacy, data protection and cyber safety, including agreements on transferring personal information beyond the EU. Some important decisions of the EU court in this area are discussed.
Module 2 Privacy enhancing technologies, 1.5 ECTS cr
The module introduces security and privacy mechanisms and technologies and proceeds to focus on how security and privacy mechanisms can be used to solve practical and theoretical problems, along with discussions of their advantages and disadvantages.
Module 3 Designing for privacy, 1.5 ECTS cr
The module introduces the foundations of privacy, data protection, and privacy enhancing technologies, and focuses on the concepts of privacy by design and privacy impact assessments by exploring the relevant background, their relationship to the foundation and fundamental human rights, and by introducing relevant methods.
Module 4 Privacy patterns for software design, 1.5 ECTS cr
The module deals with privacy aspects as part of software development. It particularly focuses on architectural tactics and patterns as reusable conceptual solutions to recurring problems in privacy protection. It also outlines how to use these concepts in agile development settings in order to engineer privacy into software.
Module 5 Artificial intelligence and data protection, 1.5 ECTS cr
This module focuses on the relationship between artificial intelligence and data protection, provides insight into the basics of artificial intelligence, and treats how to protect personal data when using various types of machine learning models. New legal obligations in European regulations concerning applications of AI and data protection are also discussed.
Progressive specialisation:
A1N (has only first‐cycle course/s as entry requirements)
Education level:
Master's level
Admission requirements
Computer Science, 30 ECTS credits, or three years of work experience in the IT sector, and upper secondary level English 6 or B, or equivalent
Selection:
Selection is usually based on your grade point average from upper secondary school or the number of credit points from previous university studies, or both.
This course is included in the following programme
- Master of Science in Industrial Engineering and Management (studied during year 4)