Entry requirements

120 credits including algorithms and data structures, database design, and 10 credits in programming. Proficiency in English equivalent to the Swedish upper secondary course English 6.

Learning outcomes

On completion of the course, the student should be able to:

• explain basic concepts, theories and principles for cybersecurity risk management,
• explain and compare model- and data-driven techniques for cybersecurity analysis,
• use model- and data-driven techniques to analyse and describe cybersecurity aspects in digital systems,
• analyze and discuss ethical aspects of computer systems security and its applications,
• present and discuss the course content orally and in writing with proficiency appropriate to the course level.

Content

This course offers an in‐depth exploration of cybersecurity analysis, beginning with foundational conceptual frameworks in risk management, adversarial and threat modelling, together with the human-social dimension of cybersecurity and the ethical aspects of security analysis. The main part of the course covers model- and data-driven techniques. Model-driven analytical techniques include, for example, how to map and analyse information flows within systems and construct attack-graphs to represent adversarial paths. Data-driven analysis methods include techniques such as reconstructing provenance graphs to trace causality, and exploiting event-correlation and anomaly‐detection algorithms to identify hidden or emergent threats. Throughout the course, students engage with use cases where theory meets practice.

Instruction

Lectures, seminars, workshops.

Assessment

The course is examined by oral and written examination spread out through the course and a written exam.

If there are special reasons for doing so, an examiner may make an exception from the method of assessment indicated and allow a student to be assessed by another method. An example of special reasons might be a certificate regarding special pedagogical support from the disability coordinator of the university.