KTH MSc in Cybersecurity

Created by Tiana Zignani

Posted 29 August 2022

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