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PhD projects

Verifiable cryptographic software

Zero-knowledge proofs are integral for deploying privacy-preserving cryptocurrencies and other blockchain applications as they represent a fundamental building block for proving statements about confidential data. The most popular framework for such proofs is based on cryptographic pairings defined over elliptic curves, where pairing-based zero-knowledge Succinct Non-Interactive Arguments of Knowledge (zk-SNARKs) underlie private transactions.

The main aim of my project is to investigate techniques to develop a formally verified efficient software library for pairing-based cryptography as means to support current blockchain projects relying on zero-knowledge proofs.

A verified implementation facilitates trust to the blockchain and increases the robustness of the system and decreases required maintenance.

This PhD project is conducted by Benjamin Salling Hvass, and it is part of DIGIT and the Concordium Blockchain Research Center.


Fast, effective and interpretable Deep Learning - Designing, training and working with artificial neural networks

Deep Learning is currently the leading paradigm in Machine Learning. It is extensively used by researchers and practitioners worldwide, showing unpreceded performance in applications like image analysis, speech/audio recognition, automatic translation and medical data analysis, to name a few. However, despite the large efforts and financial investments devoted every year in developing Deep Learning-related technologies, much of our current knowledge about these models is based on intuition. Deep Learning models are used mostly as black boxes with an enormous number of parameters that can be effectively “tuned” to memorize connections between available training samples (e.g. images or time series) to human-expert provided labels. In this project, we address two main challenges: 1) understanding neural network design (also referred to as the network architecture or its topology), training efficiency and effectiveness and 2) the interpretability of their predictions.

This PhD study conducted by Frederik Hvilshøj is supervised by Associate Professor Alexandros Iosifidis from the Department of Engineering and Professor Ira Assent from the Department of Computer Science.


Techniques to develop a formally verified efficient cryptographic library in software to support zero-knowledge proofs

Zero-knowledge proofs are integral for deploying privacy-preserving cryptocurrencies and other blockchain applications, as they represent a fundamental building block for proving statements about confidential data. The most popular framework for such proofs is based on cryptographic pairings defined over elliptic curves, where pairing-based zero-knowledge Succinct Non-Interactive Arguments of Knowledge (zk-SNARKs) underlie private transactions. The project is a collaboration between researchers from Engineering (Aranha) and Computer Science (Spitters) within DIGIT and the Concordium Blockchain Research Center to investigate techniques to develop a formally verified efficient cryptographic library in software to support zero-knowledge proofs. The PhD student on this project Benjamin Salling Hvass is partially supported by DIGIT.


Developing formally verified computer algebra algorithms

Computer Mathematics is changing the way mathematics is done. Mathematicians are using computation to "prove" theorems. However, be sure these computations are correct we need to certify these computations. This is done using interactive theorem proving. In this project, we are developing formally verified computer algebra algorithms. This is a joint project between Computer Science (Spitters) and Mathematics (Lauritzen). The PhD student on this project Andreas Aagaard Lynge is partially supported by DIGIT.


Verification framework for smart contracts

Smart contracts are small programs which carry huge amounts of money. There have been huge accidents with these programs. We are therefore developing a verification framework for smart contracts with Concordium Blockchain Research Center. The PhD student on this project Jakob Botsch Nielsen is partially supported by DIGIT.


Secure distributed systems from their cryptographic proofs to their verified implementation

Consensus algorithms are at the heart of blockchain technology. In this project, we work on precisely specifying such secure distributed systems from their cryptographic proofs to their verified implementation. This research is done with Concordium Blockchain Research Center. The PhD student on this project Søren Eller Thompson is partially supported by DIGIT.


Secure data compression and analytics for Internet of Things

The goal of the project is to design novel schemes which provide both compression and security by using the advanced signal processing techniques. The proposed schemes will be implemented in IoT devices and a prototype will be delivered. The performance of the proposed scheme will be tested and evaluated through standard randomness tests, and energy constraints and computational requirements will be considered.

This PhD study conducted by Gajraj Kuldeep is supervised by Associate Professor Qi Zhang from the Department of Engineering.


Massive-scale storage compression for a scalable IoT infrastructure

The goal of the project is to design technologies and architectures for future storage and communication systems which can handle the increased data loads, using compression to decrease the amount of data actually stored without loss of information.

This PhD study conducted by Lars Nielsen is supervised by Associate Professor Daniel Rötter from the Department of Engineering.


Massive-scale IoT dynamic data updating and compression for a scalable IoT infrastructure

This PhD project focuses on the development of novel coding theory designs for a more efficient management, updating, consistency assurance and storage of Internet of Things data at a massive scale.

In particular, focus is on the integration of (network) coding techniques and data deduplication, two approaches for reducing storage costs that have typically been attacked separately. This work is expected to open a new field at the intersection of traditional coding theory and distributed Cloud technologies and systems. The underlying goal of the results and designs of this project is to develop new technologies for Cloud, Edge and Local content management, transmission and consistency assurance.

This PhD study conducted by Niloofar Yazdani is supervised by Associate Professor Daniel Rötter from the Department of Engineering.