ACIT4280 Privacy by Design Course description

Privacy by Design is a fundamental requirement of the General Data Protection Regulation (GDPR) for all systems operating on personal information. This course provides an introduction to privacy and data protection including the legislation such as the GDPR, privacy enhancing technologies, privacy management, designing for privacy, and privacy patterns in software design. It enables the students to understand regulation, to identify privacy risk and consequences of data breaches, introduces them to privacy controls and builds skills in their application in a structured privacy engineering process.

A student who has completed this course should have the following learning outcomes defined in terms of knowledge, skills and general competence:

Knowledge

On successful completion of the course the student:

• knows the relevance of a selection of mathematical models to real-world phenomena
• has a thorough understanding of how mathematical modelling and scientific computing are utilized in various industrialized settings
• has a repertoire of methods to solve and/or analyze ordinary and partial differential equations (ODEs and PDEs)
• knows how to analyze the dynamics of an ODE system

Skills

On successful completion of this course the student can:

• derive mathematical models from facts and first principles
• apply mathematical modelling techniques on scenarios relevant to industry
• can implement mathematical models on a computer
• analyse ODE systems and use bifurcation theory to elucidate the qualitative behavior of the systems
• implement and use a selection of numerical methods for solving ODEs and PDEs

General competence

On successful completion of this course the student:

• is aware of the usefulness and limitations of mathematical modelling as well as of pitfalls frequently encountered in modelling and simulation
• is able to discuss properties of a system using the equations of the mathematical model
• can explain and use numerical methods and interpret results of numerical simulations

No formal requirements over and above the admission requirements.

Knowledge

On successful completion of this course the student has:

• knowledge of basic legal privacy concepts and data protection regulations and will be able to apply them in systems analysis and design
• knowledge of concepts of privacy by design and privacy impact assessment and the ability to compare different assessment methods
• applicable knowledge of principles of architectural tactics for privacy and privacy patterns.

Skills

On successful completion of this course the student can:

• map legal privacy principles to technical privacy concepts
• design and plan solutions that map security and privacy goals to mitigation mechanisms and technologies
• apply privacy by design and analyze software architectures using privacy impact assessments

• apply appropriate architectural tactics for privacy and privacy patterns in order to derive and create solutions that mitigate privacy risks

General competence

On successful completion of this course the student can:

• explain and apply their knowledge of security and privacy enhancing technologies

• Online course material for preparatory reading (flipped classroom approach)
• Bi-weekly lecture and case discussions
• Bi-weekly presentations of student home assignment cases

The following required coursework must be approved before the student can take the exam:

One group assignment (2-5 students appointed by teacher) consisting two parts: a report and a presentation.

Individual written digital exam, 3 hours. The exam result can be appealed.

New/postponed exam: In case of failed exam or legal absence, the student may apply for a new or postponed exam. New or postponed exams are offered within a reasonable time span following the regular exam. The student is responsible for registering for a new/postponed exam within the time limits set by OsloMet. The Regulations for new or postponed examinations are available in Regulations relating to studies and examinations at OsloMet.

None.

Grade scale A-F

The course will provide the students with an understanding of what a mathematical model is and how we use models to gain insights into systems and processes in science and engineering. The course will train the students in using analytical and computational methods for analyzing and solving differential equations and prepare them for developing, analyzing and simulating mathematical models in their own projects. The models and methods taught in this course are generic and applicable not only in science, but also in various industrial contexts.

No formal requirements over and above the admission requirements.