Course syllabus - AI-cybersecurity

Objectives

The course aims to provide students with the knowledge and skills to leverage AI and machine learning techniques to strengthen cybersecurity practices, including identifying and mitigating cybersecurity threats. 

Learning outcomes

After completing the course, the student should be able to:

1. describe and understand the fundamental concepts of AI and machine learning (ML),
2. describe and understand the application of AI and its ethical issues within the context of cybersecurity,
3. demonstrate the ability to apply AI methods and tools to identify and analyze security threats, including anomaly detection and malware classification and
4. demonstrate the ability to utilize AI for adversarial attacks. 

Course content

- Introduction to AI and ML.   
- Role and application of AI in Cybersecurity.   
- Threat detection and prevention such as malware classification, Intrusion detection and phishing detection. 
- Security problems in AI systems such as, Data poisoning, Model extraction and Adversarial attacks.    
- Ethical use of AI in Cybersecurity.   

Specific requirements

90 credits completed courses of which at least 60 credits in Computer Science, including 15 credits in programming. In addition Swedish course B/Swedish course 3 and English course A/English course 6 are required. For courses given entirely in English exemption is made from the requirement in Swedish course B/Swedish course 3.

Examination

Written assignment (INL1) 1 credit, examines the learning outcomes 1 and 2, marks Fail (U) or Pass (G). 
Seminar (SEM) 1.5 credits, examines the learning outcomes 1 and 2, marks Fail (U) or Pass (G). 
Exercise (OVN1), 5 credits, examines the learning outcomes 2, 3 and 4, marks Fail (U), 3, 4 or 5.  

A student who has a certificate from MDU regarding a disability has the opportunity to submit a request for supportive measures during written examinations or other forms of examination, in accordance with the Rules and Regulations for Examinations at First-cycle and Second-cycle Level at Mälardalen University (2020/1655). It is the examiner who takes decisions on any supportive measures, based on what kind of certificate is issued, and in that case which measures are to be applied.

Suspicions of attempting to deceive in examinations (cheating) are reported to the Vice-Chancellor, in accordance with the Higher Education Ordinance, and are examined by the University’s Disciplinary Board. If the Disciplinary Board considers the student to be guilty of a disciplinary offence, the Board will take a decision on disciplinary action, which will be a warning or suspension.

Grade

Pass with distinction, Pass with credit, Pass, Fail