KYBS5593 Network and Information Security (JSS29) (3 cr)

Study level:
Advanced studies
Grading scale:
Responsible organisation:
Faculty of Information Technology
Curriculum periods:
2017-2018, 2018-2019, 2019-2020



This course provides an introduction to network and information security. Students will study the issues involved in defining and assuring the security of information and networking systems, including many emerging applications in online social networks (OSN), Internet of Things (IoT), and Cyber Physical Systems (CPS).

Course topics covered include network security, security protocol design and analysis, security modeling, key management, intrusion detection, DDOS detection and mitigation, web security, privacy, anonymity, theoretical limitations and practical implementations and other emerging topics such as Advanced Persistent Threat in IoT and other threats in OSN.

Coursework includes a significant team project.

Completion methods

The course project requires that students execute research in network and information security. There will be a final report. Project topics will be discussed in class after the introductory material is completed. Be realistic about what can be accomplished in one week. However, the work should reflect real thought and effort. The grade will be based on the following factors: novelty, depth, correctness, clarity of presentation, and effort.

Project teams may include groups of up to three students; however, groups of greater size will be expected to make greater progress.

Learning outcomes

After successful completion of this course, students should be able to use results from security theory in practical situations and to model practical systems in theoretical terms. Students will be able to perform a risk assessment for a given system. They will be able to design policies and controls appropriate for given system requirements and will have rudimentary skills in security research.

Description of prerequisites

The students will be expected to work with mathematical models and analytical reasoning. Basic knowledge of algorithms, graph theory, and probability theory are required.

Completion methods

Method 1

Select all marked parts
Parts of the completion methods

Teaching (3 cr)

Participation in teaching
Grading scale:
No published teaching