Today identity theft is rife. The Next Generation SSI Standards project will help to strengthen the trustworthiness of the Internet by issuing people with standardised cryptographically verifiable credentials that allow relying parties to strongly identify them.
The main goal of this experiment is to integrate the Open RAN interfaces implemented by Allbesmart (EU) with the RAN Intelligent Controller (RIC) applications developed by VT (US) and validate its performance on top of the Commonwealth Cyber Initiative xG Testbed (US). The Virginia Tech team (VT) will work on an end- to- end 5G O- RAN reference implementation based on OpenAirInterface to promote innovation, especially on the near real- time RIC algorithms such as multi- user scheduling and resource allocation. The outcome of this experiment will contribute to the publicly available open-source OpenAirInterface software library with new O-RAN features towards an open and renovated 5G architecture.
This project aims to integrate the monitoring infrastructure developed by Tracking Exposed and Junkipedia to monitor the Tiktok recommendation algorithm. This new combined experimental pipeline will be used to establish if the recommender system differs across mobile and web applications.
When analysing social media platforms, their proprietary recommendation solutions are considered to be “black boxes”. The complexity and opacity of those algorithms requires to make an empirical comparison between the suggested contents on the Tiktok Web interface and its Mobile application, in order to answer our main research question.
This project aims at merging the data-based network design carried on by the University of Venice (Italy) with the advanced experimental facilities by
Northeastern University (USA) to study the backhaul network of 5G and beyond, which will radically change compared to previous generations of mobile networks. We will produce scientific results, open source code, and open data that will contribute to shape this research field in the years to come.
In this project, the goal is to develop a platform and framework for increased cybersecurity protection and end-user awareness of cyberthreats in unmanned aerial vehicles (UAV). Through AI and human-understandable decision support models, we will build and evaluate a resilient mechanism to detect malicious activities and cyber-physical threats as well as to ensure a timely incident response by drone operator. Moreover, the goal is to propose a cybersecurity-awareness protocol and ensure energy-efficient communication. This research is aimed at bridging and strengthening the EU-US cooperation in the area of AI-enabled cybersecurity between Songlab at Embry-Riddle Aeronautical University in Florida and SmartSecLab at Kristiania University College.
In this project, we aim to: (1) Interconnect the SpaceNet Testbed and its mirror at VT to examine ways in which inter-constellation connectivity can be achieved. This direct connectivity will allow us to explore future scenarios of how different mega-constellation might interconnect (e.g., OneWeb with Starlink or Telesat with Kuiper), without revealing proprietary information of each constellation, creating the equivalent of Interdomain Routing (like the Border Gateway Protocol or BGP) for space networks. (2) We will explore how mega-constellations behave in the face of failures or disruptions such as jamming and satellite takedowns. The US partner will work on the “Resilience to disruption and failures” experiment design and implementation and will highlight the importance of the constellation design/topology to build a resilient network.