Computing Technologies and Human Aspects research cluster

Developing a framework for secure Internet browsing and secure deployment of cross-platform (e.g. Java, Python, Ruby) web-applications. We put forward an idea for reducing risks of intrusions via a dynamic reconfiguration of the system software stack (OS, system and application software) so, that the most critical system software components will be replaced by alternative ones having fever number of critical forever-day vulnerabilities.

The project aims at analysing the risks of the launch vehicle crashes and spacecraft failures. We analyse orbital carrier rockets and spacecrafts launch statistics and investigate the causes of launch vehicle crashes and spacecraft failures and also analyse faults in different subsystems which led to the accidents, focusing primarily on the influence of computer-based control systems, their hardware and software components on reliability and safety of rocket-space systems.

This project aims at fast face recognition by evaluating distance between meshes of facial landmarks. The developed algorithm makes use of Google MediaPipe framework for face detection and put forward advanced techniques for face meshes normalisation, transformation and comparison offering competitive accuracy and state-of-the art performance.

Pioneering research in logic-based artificial intelligence, called Tsetlin Machine, exploiting collective behaviour of learning automata for learning patterns using propositional logic. This research aims at developing a framework for finding TM optimal hyperparameters, studying TM learning dynamic and improving explainability, visualisation and transfer-learning for Tsetlin Machines.

Energy efficiency, performance and dependability of applications running in data centers should be optimized at different levels – from developing energy-efficient applications to optimal VMs/Kubernetes allocation, dynamic tasks scheduling and proactive software rejuvenation enabling synergistic coexistence of virtual instances. The project aims at developing a framework for improving dependability, performance and energy efficiency of synergistic data centres.

Developing a framework allowing developers of large-scale distributed systems to interplay between Energy Consumption, Latency, Availability, Durability and Consistency of distributed data storages like Cassandra NoSQL. A motivation for this work is the fact that there are no known tools predicting system latency depending on the provided consistency level, number of replicas, and other essential systems parameters.

The project studies vulnerability statistics of popular software products (OSes, web servers, DBMS, web browser, etc.) and delivers a set of tools to advance on system security analysis and risk measurement and management: (i) forever-day vulnerability scanning tool, (ii) forever-day vulnerability alerting web service, (iii) intrusion avoidance guideline.

The throughput unfairness also known as performance anomaly is inherent in the very nature of mixed data rate Wi-Fi networks using the distributed coordination function. The project aims at improving Wi-fi throughput by ensuring air-time consumption fairness via optimal fragmentation, aggregation and contention window adaptation.