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AI-based Risk Assessment and Management, 7.5 Credits

AI-baserad riskbedömning och hantering, 7,5 Högskolepoäng

Established: 2023-05-02

Established by: Department of Engineering Science

Applies from: V24

Learning outcomes

After the course, the student shall be able to:

Knowledge and understanding

• show understanding of the purpose, function, and importance of risk assessment in managing cybersecurity.
• show understanding of the role of Artificial Intelligence in cyber risk assessment.
• explain common methodologies to discover system vulnerabilities.
• describe the steps and functions involved in Risk Management and their compliance with Cybersecurity standards.

Competence and skills

• devise risk assessment plans and management solutions.
• Select appropriate models for various cybersecurity risk assessment scenarios.
• discuss the role of Artificial Intelligence in cyber risk assessment.
• apply AI-driven risk assessment and management methodologies and interpret results individually and in a group.

Judgement and approach

• evaluate and manage ethical challenges when gathering personal data used to build machine-learning models.

Entry requirements

General entry requirements and approved result from the following course/courses: PFC600-Principles of cybersecurity or the equivalent.

The forms of assessment of student performance

Individual written exam. Laboratory assignment in group with oral and written reporting.

Course contents

This course introduces cybersecurity risk analysis and related AI-driven management concepts, as a foundation for cybersecurity protective mechanisms. AI-based principles and processes used for risk management methodologies are introduced. Comprehensive cybersecurity techniques are practiced to learn about means to protect industrial infrastructure assets. The implication of AI methodologies in cybersecurity management is emphasized through machine learning tasks used to assess vulnerabilities and to prioritize remedial actions to reduce cyber risk.

Other regulations

Course grading: F/Fx/E/D/C/B/A - Insufficient, Insufficient- more work required before the credit can be awarded, Sufficient, Satisfactory, Good, Very Good, Excellent

Course language: The teaching is conducted in English.

General rules pertaining to examination at University West are available at www.hv.se.

If the student has a decision/recommendation on special support due to disability, the examiner has the right to examine the student in a customized examination form.

Cycle

Second cycle

Progressive specialization

A1F - Second cycle, has second-cycle course/s as entry requirements

Main field of study

Computer Engineering, Computer Science