Arvutiteaduse instituut
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  2. 2025/26 kevad
  3. Krüptograafia ja küberturvalisuse uurimisseminar (MTAT.07.022)
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Krüptograafia ja küberturvalisuse uurimisseminar 2025/26 kevad

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Maiara Bollauf

maiara.bollauf@ut.ee

The project is suitable for MSc and PhD students interested in lattice-based security. Desired background includes linear algebra and programming skills.

Physical Layer Security in Practice

Wiretap channel communication is a fundamental model in physical-layer security that leverages information-theoretic principles to guarantee security without imposing any assumptions on the adversary’s computational capabilities. This approach is particularly relevant for 5G communications and beyond. Lattice coding offers a promising approach to secure communication over Gaussian channels, though most existing results remain largely theoretical. This project focuses on implementing a simple lattice coding scheme for low-dimensional lattices to evaluate theoretical lattice constructions in practice. The objective is to experimentally analyze performance and determine the noise conditions under which reliable communication and information-theoretic security can be achieved.


Arnis Paršovs

arnis.parsovs@ut.ee

Applied Cyber Security Topics

Applied cyber security group offers research seminar supervision on various cyber security-related topics for students who are interested in more applied research that may involve hands-on activities as well. Various hardware can be provided to students for experiments. Students who are doing applied research must still describe the research they have performed in a seminar report and convince the supervisor that the work done is worth 3 ECTS (~78 hours of work).

Students are welcome to contact Arnis Paršovs (arnis.parsovs@ut.ee) with their seminar topic ideas.

Recommended prerequisites: Applied Cryptography (MTAT.07.017) / Web Security (LTAT.04.018)

Level:BSc, MSc or PhD


Pille Pullonen-Raudvere

pille.pullonen-raudvere@cyber.ee

Secure Computation Functionalities from Function Secret Sharing

Function secret sharing is a method for securely sharing a function so that two parties can later evaluate this function and learn additively secret shared results. In theory the notion applies to all functions but in practice reasonable constructions are known for distributed point functions and distributed comparison functions. The goal of this project is to study how these functions are used to support various other operations such as machine learning activation functions like ReLu or sigmoid.

The main sources for this work are https://eprint.iacr.org/2020/1392 and https://eprint.iacr.org/2019/1095

I am also open to supervising other secure multi-party computation related topics.

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