Programme objectives

The aim of the master’s programme is to provide a broad education in cyber security with the possibility of deepening and specialising within the area of hardware-close and end user application software, communication networks, and large-scale computer systems. The programme includes both theoretical foundations as well as the practical ability to develop secure products and systems.

The programme will provide the students with abilities to participate and lead work within evaluation, development and implementation of secure computer and software technology.

Knowledge and understanding

For the degree of Master of Science from the programme cyber security, the student shall

demonstrate knowledge and understanding within computer science and engineering, including broad knowledge as well as significantly deepened knowledge within cyber security, and deepened understanding of active research and development work
demonstrate deepened understanding of the methodology and the scientific perspective within computer science and engineering
demonstrate knowledge and understanding in social, ethical, and environmental sustainability within cyber security.

Skills and abilities

For the degree of Master of Science from the programme cyber security, the student shall

demonstrate good analytical problem-solving ability
demonstrate ability to independently define and solve construction problems within computer science from a security perspective in combination with other technical and non-technical requirements with respect to peoples’ abilities and needs and societal goals for economic, social, environmental sustainability
demonstrate requisite skills and abilities to participate in and develop practices implemented in private and public organisations, as well as in academic research
demonstrate the ability in speech and writing to report clearly and discuss his or her conclusions and the knowledge and arguments on which they are based in dialogue with different audiences.

Ability to make judgments and adopt a standpoint

For the degree of Master of Science from the programme cyber security, the student shall

demonstrate ability to assess quality of scientific studies and ability to reflect critically review academic and non-academic texts
through self-driven personal development be able to maintain the ability to life-long learning
from a cyber security perspective demonstrate ability to relate and judge technology and technology-related behaviour in society according to equality, diversity, social, ethical and environmental sustainability and to contribute in discussions on these topics.

Extent and content of the programme

The master's programme in cyber security is 120 credits at advanced level, corresponding to two years of full-time studies. The programme is given in English.

The programme contains 39,5 credits of mandatory courses, at least 30 credits of conditionally elective courses, 30 credits of master thesis project, and 20,5 credits elective courses.

Individual exceptions from this can be approved by the programme director if there are special circumstances (e.g. exchange studies).

Eligibility and selection

General admission requirements and the following special admission requirements must be fulfilled in order to be admitted to the programme:

Bachelor's degree in computer science, computer networking, software engineering, applied mathematics or equivalent.
Courses in mathematics (of at least 5 credits each) in the following areas; calculus in one variable, linear algebra, statistics and probability theory, and discrete structures.
Courses in computer science (of at least 5 credits each) in both programming and algorithms and data structures.

It is recommended to have taken a course in operating systems and in communication networks.

Within the programme there may be courses with additional entry requirements. The requirements are stated under the heading "Specific prerequisites" in the syllabus. Examples include the following:

A continuation course in algorithmic complexity (in addition to the basic course in algorithms and data structures) is a specific prerequisite for the conditionally elective course in foundations of cryptography.
Digital technology is a specific prerequisite for the conditionally elective course in hardware security.
Computer Science/Hardware is a specific entry requirement for the recommended course in Operating Systems.
Multivariable calculus is a specific prerequisite for the optional/recommended courses in machine learning.

The selection process is based on the following criteria: Study results (grades, relevant subjects and English), motivation for studies (motivation letter, references, courses and relevant work experience) and prior education.

Prior education is evaluated based on the quality and suitability of the subjects that are relevant for the applied program. For international prior education, university ranking is also part of the merit rating. The merit rating is carried out on a scale of 1-75.

For students admitted to a 5-year engineering programme at KTH with a place guarantee to this programme, the programme's eligibility requirements are met by the following courses within the respective programme. The course codes refer to admission year 2022 on the 5-year engineering programme and may vary for other admission years.

Degree Programme in Computer Science and Engineering (CDATE)

Mandatory courses:

SF1625 Calculus in One Variable
SF1624 Algebra and Geometry
SF1935 Probability Theory and Statistics with Application to Machine Learning
SF1688 Discrete Mathematics
DD1337 Programming
DD1338 Algorithms and Data Structures

Degree Programme in Information and Communication Technology (CINTE)

Mandatory courses:

SF1625 Calculus in One Variable
SF1624 Algebra and Geometry
SF1912 Probability Theory and Statistics
SF1610 Discrete Mathematics
ID1018 Programming I
ID1021 Algorithms and Data Structures

Degree Programme in Engineering Mathematics (CTMAT)

Mandatory courses:

SF1673 Analysis in one variable
SF1672 Linear Algebra
SF1918 Probability Theory and Statistics
SF1679 Discrete Mathematics
DD1331 Fundamentals of Programming
DD1320 Applied Computer Science

Degree Programme in Engineering Physics (CTFYS)

Mandatory courses:

SF1673 Analysis in one variable
SF1672 Linear Algebra
SF1922 Probability Theory and Statistics
DD1331 Fundamentals of Programming
DD1327 Fundamentals of Computer Science

In addition, the following prior knowledge needs to be acquired as an elective course:

Discrete Mathematics.

Implementation of the education

Structure of the education

Each academic year consists of two semesters which are 20 weeks each, and each semester is further divided into two study periods.

The first year contains mandatory courses in an introductory block of 22,5 credits in total as well as one course of 7,5 credits in sociotechnical aspects of cybersecurity. It is also mandatory to take 7,5 credits in Theory and Methodology of Science.

In addition to the mandatory courses, it is required to select at least 30 credits of a number of advanced courses in cyber security, and 22,5 credits are freely elective and the programme has a number of recommended courses that can be choosen. The programme ends with a mandatory thesis project of 30 credits.

Courses

The programme is course-based. Lists of courses are included in appendix 1.

Grading system

Courses in the first and the second cycle are graded on a scale from A to F. A-E are passing grades, A is the highest grade. The grades pass (P) and fail (F) are used for courses under certain circumstances.

Conditions for participation in the programme

Participation requires admission to courses within the programme and course registration.

For further studies, special admission requirements for the course are to be fulfilled. Special admission requirements are listed in the respective course syllabus.

Degree project

The degree project is the final part of the education. The project work may begin when special admission requirements for the course are fulfilled.

Degree

Degree is entitled Teknologie masterexamen/Master of Science. The main field of study is stated in the text on the degree certificate. The text on the degree certificate states the educational programme completed by the student.

Appendix 1: Course list

Appendix 2: Specialisations

General Courses

Study year 1

Mandatory courses (39.5 hp)

Course code	Course name	Credits	Edu. level
AK2030	Theory and Methodology of Science (Natural and Technological Science)Can be taken in any period during the programme	4.5 hp	Second cycle
DA2215	Theory of Science and Scientific methods in CybersecurityCan be taken in any period during the programme	3.0 hp	Second cycle
DD2303	The Cybersecurity Engineer's Role in Society	2.0 hp	Second cycle
DD2391	Cybersecurity Overview	7.5 hp	Second cycle
DD2510	Cybersecurity in a Socio-Technical ContextCan be read in year 1 or year 2	7.5 hp	Second cycle
DD2520	Applied Cryptography	7.5 hp	Second cycle
EN2720	Ethical HackingCan be taken in year 2 if you choose to read EP2120	7.5 hp	Second cycle

Conditionally elective courses

Course code	Course name	Credits	Edu. level
DD2448	Foundations of Cryptography	7.5 hp	Second cycle
DD2496	Privacy Enhancing Technologies	7.5 hp	Second cycle
DD2497	Project course in System Security	7.5 hp	Second cycle
DD2525	Language-Based Security	7.5 hp	Second cycle
EL2850	Cyber-Physical Security in Time-Critical Systems	7.5 hp	Second cycle
EP2500	Networked Systems Security	7.5 hp	Second cycle
EP2510	Advanced Networked Systems Security	7.5 hp	Second cycle
EP2520	Building Networked Systems Security	7.5 hp	Second cycle
EP2780	Digital forensics and incident response	7.5 hp	Second cycle
EP2790	Security Analysis of Large-Scale Computer Systems	7.5 hp	Second cycle
ID2218	Design of Fault-tolerant Systems	7.5 hp	Second cycle
IL1333	Hardware Security	7.5 hp	First cycle

Recommended courses

Course code	Course name	Credits	Edu. level
DD1420	Foundations of Machine LearningOverlaps with DD2421	7.5 hp	First cycle
DD2421	Machine LearningOverlaps with DD1420	7.5 hp	Second cycle
DD2424	Deep Learning in Data Science	7.5 hp	Second cycle
DD2434	Machine Learning, Advanced Course	7.5 hp	Second cycle
DD2437	Artificial Neural Networks and Deep Architectures	7.5 hp	Second cycle
DD2440	Advanced Algorithms	6.0 hp	Second cycle
DD2443	Parallel and Distributed Computing	7.5 hp	Second cycle
DD2447	Statistical Methods in Applied Computer Science	6.0 hp	Second cycle
DD2459	Software Reliability	7.5 hp	Second cycle
DD2585	Programmable Society with Blockchains and Smart Contracts	7.5 hp	Second cycle
DD2610	Deep Learning, advanced course	7.5 hp	Second cycle
DH2628	Interaction Design Methods	7.5 hp	Second cycle
EL2805	Reinforcement Learning	7.5 hp	Second cycle
EP2120	Internetworking	7.5 hp	Second cycle
ID1206	Operating Systems	7.5 hp	First cycle

Supplementary information

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.

Information regarding conditionally elective courses

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

Study year 2

Mandatory courses (54.5 hp)

Course code	Course name	Credits	Edu. level
AK2030	Theory and Methodology of Science (Natural and Technological Science)The course can be read in any period during the programme.	4.5 hp	Second cycle
DA2215	Theory of Science and Scientific methods in CybersecurityThe course can be read in any period during the programme.	3.0 hp	Second cycle
DA237X	Degree Project in Computer Science and Engineering, specialising in Cybersecurity	30.0 hp	Second cycle
DD2303	The Cybersecurity Engineer's Role in Society	2.0 hp	Second cycle
DD2510	Cybersecurity in a Socio-Technical ContextCan be read in year 1 or year 2	7.5 hp	Second cycle
EN2720	Ethical HackingCan be read in year 2 if you choose to read EP2120	7.5 hp	Second cycle

Conditionally elective courses

Course code	Course name	Credits	Edu. level
DD2448	Foundations of Cryptography	7.5 hp	Second cycle
DD2460	Software Safety and Security	7.5 hp	Second cycle
DD2482	Automated Software Testing and DevOps	7.5 hp	Second cycle
DD2496	Privacy Enhancing Technologies	7.5 hp	Second cycle
DD2497	Project course in System Security	7.5 hp	Second cycle
DD2525	Language-Based Security	7.5 hp	Second cycle
EL2850	Cyber-Physical Security in Time-Critical Systems	7.5 hp	Second cycle
EP2500	Networked Systems Security	7.5 hp	Second cycle
EP2510	Advanced Networked Systems Security	7.5 hp	Second cycle
EP2520	Building Networked Systems Security	7.5 hp	Second cycle
EP2780	Digital forensics and incident response	7.5 hp	Second cycle
EP2790	Security Analysis of Large-Scale Computer Systems	7.5 hp	Second cycle
ID2218	Design of Fault-tolerant Systems	7.5 hp	Second cycle
IL1333	Hardware Security	7.5 hp	First cycle

Recommended courses

Course code	Course name	Credits	Edu. level
DD1420	Foundations of Machine LearningOverlaps with DD2421	7.5 hp	First cycle
DD2421	Machine LearningOverlaps with DD1420	7.5 hp	Second cycle
DD2424	Deep Learning in Data Science	7.5 hp	Second cycle
DD2434	Machine Learning, Advanced Course	7.5 hp	Second cycle
DD2437	Artificial Neural Networks and Deep Architectures	7.5 hp	Second cycle
DD2440	Advanced Algorithms	6.0 hp	Second cycle
DD2443	Parallel and Distributed Computing	7.5 hp	Second cycle
DD2447	Statistical Methods in Applied Computer Science	6.0 hp	Second cycle
DD2459	Software Reliability	7.5 hp	Second cycle
DD2528	Dependable Autonomous Systems	7.5 hp	Second cycle
DD2585	Programmable Society with Blockchains and Smart Contracts	7.5 hp	Second cycle
DD2601	Deep Generative Models and Synthesis	7.5 hp	Second cycle
DD2610	Deep Learning, advanced course	7.5 hp	Second cycle
DH2628	Interaction Design Methods	7.5 hp	Second cycle
EG2130	Communication and Control in Electric Power Systems	7.5 hp	Second cycle
EL2805	Reinforcement Learning	7.5 hp	Second cycle

Supplementary information

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.

Information regarding conditionally elective courses

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

This programme has no specialisations.

Studies

Support and guidance

IT and digital services

Contact

Programme objectives

Knowledge and understanding

Skills and abilities

Ability to make judgments and adopt a standpoint

Extent and content of the programme

Eligibility and selection

Implementation of the education

Structure of the education

Courses

Grading system

Conditions for participation in the programme

Degree project

Degree

General Courses

Study year 1

Mandatory courses (39.5 hp)

Conditionally elective courses

Recommended courses

Supplementary information

Information regarding conditionally elective courses

Study year 2

Mandatory courses (54.5 hp)

Conditionally elective courses

Recommended courses

Supplementary information

Information regarding conditionally elective courses