KTH MSc in Cybersecurity

The growth of dependence on digital infrastructures in society has made cyberattacks more dangerous if they occur on power grids, financial systems and communication infrastructure. The KTH master's programme in cybersecurity aims to develop the cybersecurity engineers of tomorrow.

Cybersecurity is a broad and multi-faceted topic ranging form fundamental computing theory to software engineering, computer communication, large-scale distributed systems, and physical process control into human and social behaviour. This programme is anchored in computer science and extends to business and social aspects of cybersecurity.

This programme is taught entirely in English.

Curriculum

The KTH MSc in Cybersecurity is a two-year programme split across three semester of courses and a final semester dedicated to the master's degree project. Each semester consists of approximately 30ECTS credits. Below is a breakdown of the courses to expect in each year.

Year 1

The course AK2030 Theory and Methodology of Science is compulsory and can be taken at any point during the programme, however, it is recommended to take it during period 1 in parallel with the science module in the course DD2302.

Mandatory courses

• Theory and Methodology of Science (Natural and Technological Science)
• Theory of Science and Scientific methods in Cybersecurity
• The Cybersecurity Engineer's Role in Society
• Cybersecurity Overview
• Cybersecurity in a Socio-Technical Context
• Applied Cryptography
• Ethical Hacking
   

Conditionally elective courses

At least 30 credits of conditionally elective courses must be taken.

• Foundations of Cryptography
• Privacy Enhancing Technologies
• Project course in System Security
• Language-Based Security
• Cyber-Physical Security in Time-Critical Systems
• Networked Systems Security
• Advanced Networked Systems Security 
• Building Networked Systems Security
• Digital forensics and incident response 
• Security Analysis of Large-Scale Computer Systems 
• Design of Fault-tolerant Systems
• Hardware Security

Recommended courses

• Foundations of Machine Learning
• Deep Learning, Advanced Course
• Machine Learning
• Deep Learning in Data Science
• Machine Learning, Advanced Course
• Artificial Neural Networks and Deep Architectures
• Advanced Algorithms
• Parallel and Distributed Computing
• Statistical Methods in Applied Computer Science
• Interaction Design Methods
• Communication and Control in Electric Power Systems
• Reinforcement Learning

Year 2

Mandatory courses

• Theory and Methodology of Science (Natural and Technological Science)
• Theory of Science and Scientific methods in Cybersecurity
• Degree Project in Computer Science and Engineering, specialising in Cybersecurity
• The Cybersecurity Engineer's Role in Society
• Cybersecurity in a Socio-Technical Context

Conditionally elective courses

At least 30 credits of conditionally elective courses must be taken.

• Foundations of Cryptography
• Software Safety and Security
• Automated Software Testing and DevOps
• Privacy Enhancing Technologies
• Project course in System Security
• Language-Based Security
• Cyber-Physical Security in Time-Critical Systems
• Networked Systems Security
• Advanced Networked Systems Security
• Building Networked Systems Security
• Digital Forensics and Incident Response
• Security Analysis of Large-Scale Computer Systems
• Design of Fault-tolerant Systems
• Hardware Security

Recommended courses

• Foundations of Machine Learning
• Deep Learning, Advanced Course
• Machine Learning
• Deep Learning in Data Science
• Machine Learning, Advanced Course
• Artificial Neural Networks and Deep Architectures
• Advanced Algorithms
• Parallel and Distributed Computing
• Statistical Methods in Applied Computer Science
• Dependable Autonomous Systems
• Interaction Design Methods
• Communication and Control in Electric Power Systems
• Reinforcement Learning

Eligibility

A bachelor's degree or comparable qualification equivalent to a Swedish bachelor's degree from an internationally recognised university is required. For this programme, a bachelor's degree in computer science, computer networking, software engineering, applied mathematics or equivalent is required. The bachelor's degree must have had courses in mathematics with at least 5 ECTS credits in calculus in one variable, linear algebra, statistics and probability theory, and discrete structures as well as computer science courses with at least 5 ECTS credits in programming and algorithms and data structures.

Additionally, applicants will need to demonstrate their English language proficiency. This can be done by achieving the following scores in the following internationally recognised English tests:

• IELTS Academic/IELTS UKVI: An overall score of 6.5, with no section lower than 5.5
• TOEFL iBT: Score of 20 (scale 0-30) in written test, total score of 90. We accept TOEFL iBT Special Home Edition Test. We do not accept TOEFL ITP, TOEFL iBT MyBest, Institutional TOEFL, TOEFL Essentials, or the revised TOEFL Paper-delivered Test.
• Cambridge Michigan Language Assessments: University of Michigan, Examination for the Certificate of Proficiency in English (ECPE)
• Pearson PTE Academic: Score of 62 (writing 61)
• Cambridge ESOL: C1 Advanced (CAE), minimum overall score 180 (points awarded since 2015), or Cambridge English certificate level C1, minimum score 180, or Cambridge English: Advanced