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Modern topics in telecommunications and radio engineering 10 – Intelligent security

Individual course

Max amount of FITech students: 20

Persons without a valid study right at a Finnish university or university of applied sciences have preference to this course.

In this course we will introduce the requirements for security in future self-sustaining wireless networks that are defined with native, embedded artificial intelligence (AI) capability, where new security paradigms are crucial to address novel and unprecedented threat vectors. We will cover the opportunities of introducing intelligence into the security definitions by presenting novel approaches from the perspective of different layers.

Course contents

  • Challenges towards 6G security including 6G vision, architecture, intelligence and trustworthiness.
  • Tools for achieving intelligence in network security: ENISA recommendations, ORAN security, proactive and reactive network security, federated learning, moving target defense and explainable AI algorithms.
  • Physical layer security: motivation and roadmap.
  • Confidentiality issues and techniques.
  • Physical layer authentication mechanisms, classical system and stages and ML-based solutions.
  • Secret Key Generation: SKG standard procedure, secret key rate and protection against active attacks.

Learning outcomes

After successfully completing this course, the student can

  • identify the threat landscape towards future wireless networks.
  • differentiate physical layer security and network security techniques, their challenges and limitations, and their practical aspects.
  • explain different intelligent security approaches, their challenges and strengths.
  • evaluate the performance of security solutions based on physical layer security and network security.
  • apply machine learning tools and provide their explainability for the design of intelligent security solutions.

Course material

  • Zero-touch network and Service Management (ZSM); General Security Aspects. ETSI GR ZSM 010 V1.1.1, 2021. Online available here.
  • Evolution of 5G Cyber Threats and Security Solutions, INSPIRE-5Gplus whitepaper, March 2022. Online available here.
  • Osorio, D.P., Sánchez, J.D. and Alves, H. (2019). Physical-Layer Security for 5G and Beyond. In Wiley 5G Ref (eds R. Tafazolli, C.-L. Wang and P. Chatzimisios). Online available here.
  • Shakiba-Herfeh, M., Chorti, A., Vincent Poor, H. (2021). Physical Layer Security: Authentication, Integrity, and Confidentiality. In: Le, K.N. (eds) Physical Layer Security. Springer, Cham. Online available here.
  • Software: Matlab/Phyton

Teaching schedule

  • Lectures on Tuesday and Thursday 14.3.–2.5.2023 (recordings in Moodle)
  • Exam TBD (in Moodle, check the date from University of Oulu study guide)

Completion methods

The course can be completed online.

Lectures 23 h, independent work (literature review + self-study) 70 h, research seminar (individual or group) 20 h, assignments (individual or group) 22 h and exam preparation 20 h.

Grading:

  • Assignments: simulation exercises (individual and in groups) 20 %
  • Research seminar 20 %
  • Final exam 60 %

More information in the University of Oulu study guide.

You can get a digital badge after completing this course.

Responsible teacher

University of Oulu
Diana Moya Osorio
University of Oulu
Pawani Porambage

Further information about the course and studying

University of Oulu
Johanna Vartiainen

Contact person for applications

FITech Network University
Fanny Qvickström, Student services specialist
Start here
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Category:
ICT Studies,
Technical studies
Topics:
5G technology,
AI and machine learning,
Information security,
Internet technology,
Wireless technology
Course code:
521200S
Study credits:
5 ECTS
Price:
0 €
Course level:
Teaching period:
13.3.–8.5.2023
Application start date:
07.11.2022
Application deadline:
5.3.2023
Host university:
University of Oulu
Who can apply:
Adult learner,
Degree student
Teaching method:
Online
Teaching language:
English
General prerequisites:
Knowledge of wireless communications, probability, communication theory, protocols and computer networks
Course suitable for:
Adult learners who have previous studies or work experience in communications. Master's students or comparable in communications
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