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KTH MSc in Cybersecurity

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 two-year KTH Master's programme in Cybersecurityaims to develop the cybersecurity engineers of tomorrow.

Cybersecurity is a broad and multi-faceted topic ranging from 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.

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. This programme is taught entirely in English.

Year 1

The mandatory courses AK2030 Theory and Methodology of Science and DA2215 Theory of Science and Scientific methods in Cybersecurity can be taken at any period during the programme.

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

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

  • Privacy Enhancing Technologies 
  • Cyber-Physical Security in Time-Critical Systems 
  • Advanced Networked Systems Security 
  • Digital forensics and incident response 
  • Networked Systems Security 
  • Cybersecurity Threat Modelling and Risk Analysis 
  • Foundations of Cryptography 
  • Language-Based Security 
  • Building Networked Systems Security 
  • Design of Fault-tolerant Systems 
  • Hardware Security 
  • Project Course on Operating Systems and Compiler Support for Security 

Recommended courses

  • Programmable Society with Blockchains and Smart Contracts 
  • Ecological Economics 
  • Foundations of Machine Learning 
  • Machine Learning, Advanced Course 
  • Artificial Neural Networks and Deep Architectures 
  • Advanced Algorithms 
  • Parallel and Distributed Computing 
  • Statistical Methods in Applied Computer Science 
  • Deep Learning, advanced course 
  • Reinforcement Learning 
  • Internetworking 
  • Operating Systems 
  • Environmental Management 
  • Machine Learning 
  • Deep Learning in Data Science 
  • Interaction Design Methods 
  • Software Reliability 

Year 2

he mandatory courses AK2030 Theory and Methodology of Science and DA2215 Theory of Science and Scientific methods in Cybersecurity can be taken at any period during the programme.

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

Mandatory courses

  • The Cybersecurity Engineer's Role in Society 
  • Degree Project in Computer Science and Engineering, specialising in Cybersecurity, Second cycle 

Conditionally elective courses

  • Foundations of Cryptography 
  • Software Safety and Security 
  • Language-Based Security 
  • Building Networked Systems Security 
  • Design of Fault-tolerant Systems 
  • Hardware Security 
  • Automated Software Testing and DevOps 
  • Privacy Enhancing Technologies 
  • Cyber-Physical Security in Time-Critical Systems 
  • Networked Systems Security 
  • Advanced Networked Systems Security 
  • Digital forensics and incident response 
  • Project Course on Operating Systems and Compiler Support for Security 
  • Cybersecurity Threat Modelling and Risk Analysis 

Recommended courses

  • Foundations of Machine Learning 
  • Machine Learning 
  • Machine Learning, Advanced Course 
  • Artificial Neural Networks and Deep Architectures 
  • Advanced Algorithms 
  • Statistical Methods in Applied Computer Science 
  • Dependable Autonomous Systems 
  • Programmable Society with Blockchains and Smart Contracts 
  • Deep Generative Models and Synthesis 
  • Deep Learning, advanced course 
  • Reinforcement Learning 
  • Parallel and Distributed Computing 
  • Deep Learning in Data Science 
  • Software Reliability 
  • Interaction Design Methods 
  • Communication and Control in Electric Power Systems 

Admission requirements

Bachelor's degree: Academic qualifications from an internationally recognised university equivalent to a Swedish bachelor's degree.

English proficiency: equivalent to the Swedish upper secondary course English 6/English Level 2.

Specific requirements for Cybersecurity: A bachelor’s degree in computer science, computer networking, software engineering, applied mathematics or equivalent, corresponding to 180 ECTS credits, including courses in:

  • Mathematics: courses (of at least 5 ECTS credits each) in the following areas; calculus in one variable, linear algebra, statistics and probability theory and discrete structures
  • Computer Science: courses (of at least 5 ECTS credits each) in both programming and algorithms and data structures
  • It is recommended to have taken courses in operating systems and communication networks

Application deadlines 

For studies starting August 2027:

  • 16 October (2026): Application opens
  • 15 January: Last day to apply
  • 1 February: Submit documents and, if required, pay application fee
  • 1 April: Admission results announced

Training Offer Details

Digital technology / specialisation
Training opportunities
Learning Effort
Full time
Self-paced
No
Duration Time
2 Years
Digital skill level
Geographic scope - Country
Sweden
Target language
English
Field of education and training
Information and communication technologies not elsewhere classified
Is this course free
No
Course Amount
32508.00€
Credential offered
Qualification Award
Prerequisites
No
Upcoming course
No