<h2><a target="_blank" rel="noopener noreferrer" href="https://tnc23.geant.org/">TNC23 conference 5 - 9 June in Tirana, Albania

During the Covid crisis I followed my course using Microsoft Teams. In many cases the video/audio quality was really bad, and yet none of the speed tests I ran showed any abnormality. What happened? At that time, speed test websites only measured throughput. Latency is measured as well, but as idle latency (without load on it). However, when you attend a class/meeting there are always other apps/people using your network.

We need a way to measure working latency. The IETF has started to develop a new measurement technique called RPM to measure latency under working conditions. Our goal is to implement it in a browser so that every user will know why their connection is poor. Moreover, all current tests work with TCP connections. With TCP it is possible to send a large amount of data, but it's very hard to accurately measure latency or packet losses. Meanwhile, many cloud providers are moving towards HTTP/3 with the QUIC protocol. Therefore, we are developing our measurement tool with QUIC.

https://youtu.be/IySU1TIualE

APK Falcon is a tool to assist users in assessing the impact of mobile apps on privacy, to improve knowledge and empower decision making in accordance with the values of the EU Next Generation Internet. APK Falcon will help users understand the permission system, leading to improved management - such as revoking highly intrusive permissions or being more cautious when asked to grant permission. This tool will be made in a user-centric way, so the impact on privacy can be understood by everyone.

Users will be able to access a web service where they can search for the name of an application and obtain a privacy score, as well as information to understand this score. APK Falcon can assist users in making more informed decisions about granting permissions and managing their privacy. By shedding light on the permission system, APK Falcon can empower users to take control of their privacy in a simple, open and transparent fashion.

https://youtu.be/yfmBsHfokRc

The transition to renewable energy is critical to mitigate the effects of climate change and achieve a sustainable future. One promising approach to advance this transition is through the development of Renewable Energy Communities (RECs). These communities are formed by groups of people or organisations that come together to produce, consume and share renewable energy locally. They are designed to promote local ownership, collaboration and innovation in the deployment of renewable energy technologies.

To fully realise the potential of these communities, assessing their value and impact is essential. This assessment will provide insights into the benefits and challenges associated with RECs, and help identify best practices for their development and implementation. It will also evaluate the economic benefits of these communities, including the potential for job creation, increased economic activity and cost savings for participants.

https://youtu.be/oFkGKTDpGqQ

Research shows that Artificial Intelligence (AI) can be an effective tool for automated cyber threat hunting. However, the lack of explainability still prevents its mass deployment into commercial-grade tools. Due to AI complexity it's hard to get reasons behind its output, which are crucial for cyber security incident handling and response. We thus bring new design principles of AI by dividing complex monolithic models into small components with defined functionality. By observing the outputs and interaction of these components, we can get an insight into their internal behaviour and provide explanations and reasoning behind their output. The lack of explainability originates from AI's enormous complexity, which people cannot comprehend. We thus divide the complex AI into a component-based system, each component designed separately, like in the human brain. In the brain, there are parts responsible for vision and other parts for hearing for example. We know which part is responsible for what, dramatically increasing our understanding of such a complex system.

Component-based models are solutions for AI model deployment in cyber security and other high-stakes areas where explanations are necessary. The division into components provides better control over the predictions and explains them. The improved explainability also reduces the chance of design errors, can improve model quality control and increases the overall trust of its users. Moreover, we can use reasoning to filter out obvious mistakes and increase AI reliability.

https://youtu.be/Cbov_mjxyqE

Secure computer networks rely on monitoring, threat detection and security operators who respond to automatically created alerts. Performance of current anomaly and threat detection methods is dependent on the network telemetry data they are developed on. However, in some cases network telemetry does not contain truthful information. An error can occur during transmission, or an attacker can spoof information to confuse threat detectors. As a result, many attacks may remain undetected and false alerts might overwhelm security personnel. We are currently exploring an approach that utilises a combination of several data sources to overcome imperfections.

Many state-of-the-art detectors are based on Machine Learning (ML) technology, which can be easily confused. Attackers can alter traffic shape by sending additional data which is unnecessary for communication. Malicious traffic can be completely hidden by this technique and missed by the ML - an outgoing attack might not be detected at all. Data incompleteness is another problem. For example, no blocklist can ever contain every malicious IP address. Moreover, these IP addresses can change over time. Therefore the output of some detectors might not reflect reality. Current techniques, when used separately, are suffering from many pitfalls.

https://youtu.be/z2_Gre0wNdA

In recent years there has been a major development in the field of cluster computing. These solutions often require many dedicated resources to communicate with each other, and bind their abilities in a collaborative manner. There is also a requirement to allow multiple users to use a single cluster without affecting each others' computations. Nowadays, the FPGAs provide an excellent scalability and programmability for this purpose, with the advantage of parallelism and achieved throughput.

This talk introduces the design of a generalised streaming library for the PCI Express interface called JetStream 2.0. It is an enhancement of the previous generation, able to run at the data rates of PCI Express Gen3 x16, that means reaching the transfer speeds of up to 100Gbps. The architecture also supports sending data between two FPGA cards using a zero-copy mechanism - which bypasses the classical buffering of data in RAM and sends them directly to the addressed device. This solution is proposed as vendor independent, thus FPGA cards both from Intel and AMD/Xilinx can be used and also mixed on the host.

https://youtu.be/DMPzoBAnln0

https://youtu.be/PRd_tAF1QRU

https://youtu.be/y7v71zk9FIg

A Community of Practice (CoP) is a group of people who share a concern or a passion for something they do, learning how to do it better as they interact regularly. vCoP is an online CoP connected through technology and, in this instance, on an Enterprise Social Network (ESN). An ESN is a social network used in enterprise settings to bring together people who share the same interests - using the platform to engage and improve knowledge collectively. It is regarded as Enterprise 2.0. Coming together as a community and working as a unit may help encourage and strengthen the knowledge economy - decreasing isolation and increasing connection, communication and collaboration.

https://youtu.be/9s4FXIE5vEM

Research has highlighted that although learning about cultural heritage still relies on text and pictures, physical objects are more effective, extending beyond conceptual experiences. Virtual representations of 3D objects cannot often support the attributes of physicality that may be valuable, for instance, in the reconstruction processes of a monument.

Margherita's research proposes the creation of accessible digital archives and their dissemination and valorisation. The main case study will examine the Church of St. Augustine and the Oratory of Blessed Becchetti in Fabriano, Italy, abandoned after an earthquake in 2016. The church has undergone numerous restorations, but historical evidence allows insight in to its original forms. The digital archive will give easy access to the models of the reconstructive hypotheses, using innovations in research and development in the practice of cultural heritage to ensure high-resolution images, metadata and 3D models. These tools enable us to learn more about abandoned places through the dissemination of content and information, promoting the preservation of the architectural and artistic heritage.

Models will be available for download, editing, and 3D printing for interdisciplinary uses, dedicated to visually impaired people, useful for the process of study and comprehensive tactile perception for students, curious people and scholars.

https://youtu.be/xYr8Mjb7Di4

Nowadays, the amount of data stored on digital devices is huge and this trend is rising. Because of data protection regulation, and to deter attacks, sensitive data must be protected proactively.

Furthermore, recent legislation, among which the General Data Protection Regulation (EU GDPR) and the Consumer Data Right (CDR), has started to mandate technical measures for data protection. In particular, the principle of “data minimisation” states that a data controller should limit the collection of personal information to what is directly relevant and necessary to accomplish a specified purpose. The principle of minimisation can be implemented by limiting access to certain categories of data according to the experts that have to use the data.

This research project identified a technological gap related to the data minimisation principle. Although the GDPR legislation provides guidelines, it does not explicitly specify the required techno- logical tools to implement them. The project aims to fill that gap by developing a cryptographic scheme as a service integrated within a cloud system.

An encrypted database offers intrinsic data security. Data is transformed into ciphertext (unreadable text) using a cryptographic procedure. Even when an attack on the database would be successful, the encryption techniques prevent hackers to analyze or decrypt your data to use it to their ad- vantage. Specifically, the cryptographic technique that is chosen is Attribute-Based Encryption (ABE). ABE encrypts a resource against attributes instead of concrete users. Only users that possess a correct combination of attributes will be able to decrypt the resource. ABE eases the implementation of access control rules to comply with the GDPR principles.

Finally, the last part of the project consists of implementing the cryptographic scheme as a cloud service. Because the cloud is one of the most popular methods for storing data among large communities, we want to integrate the ABE system with cloud storage and other potential cloud services. The envisioned system will integrate the existing Role-Based Access Control (RBAC) system of a cloud system with ABE, allowing data to be encrypted using pre-existing privileges.

https://youtu.be/GbnUsx65dVU

Archived FTP Lightning Talks

Traffic analysis of communication and collaboration apps bloomed with Covid-19 via advanced Deep Learning approaches -  Idio Guarino (University of Naples Federico II) GARR

Roman Emperors and Facial Recognition - Karel van Klink (GÉANT)

Self-Sovereign Identity (SSI) for Future-Proof Digital Wallets - Frederic Gerber (SWITCH)

Multi-factor authentication support between eduGAIN federations - Hilco de Lathouder (SURF)

Guessing PINs, One Partial PIN at a Time - Ashley Sheil (Maynooth University)HEANET

Challenges in processing and knowledge discovery in specifications of scientific resources - Witold Taisner (Poznan Supercomputing and Networking Center)PSNC

Archived FTP Lightning Talks