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Section: Partnerships and Cooperations
European Initiatives
EIT Digital CREEP2
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Other partners: Expert Systems (IT), Inria (FR), Engineering (IT)
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Abstract: Project CREEP (Cyberbulling Effects Prevention) aims at identifying and preventing the possible negative impacts of cyberbullying on young people. It seeks to realise advanced technologies for the early detection of cyberbullying phenomena through the monitoring of social media and the communication of preventive advices and personalized recommendations tailored to adolescents’ needs through a virtual coaching system (chatbot).
JPI CH READ-IT
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Project title: Reading Europe Advanced Data Investigation Tool
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Other partners: CNRS-IRISA (FR), Open University (UK), Universiteit Utrecht (NL), Institute of Czech Litterature (CZ)
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Abstract: READ-IT is a transnational, interdisciplinary R&D project that will build a unique large-scale, user- friendly, open access, semantically-enriched investigation tool to identify and share groundbreaking evidence about 18th-21st century Cultural Heritage of reading in Europe. READ-IT will ensure the sustainable and reusable aggregation of qualitative data allowing an in-depth analysis of the Cultural Heritage of reading. State-of-the art technology in Semantic Web and information systems will provide a versatile, end-users oriented environment enabling scholars and ordinary readers to retrieve information from a vast amount of community-generated digital data leading to new understanding about the circumstances and effects of reading in Europe.
CHIST-ERA ID_IOT
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Coordinator: Boris Skoric (Eindhoven Univ. of Technology (NL))
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Other partners: Inria-RBA (Teddy Furon, Marzieh Gheisari Khorasgani), Univ. of Geneva (CH)
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Abstract: The IoT will contain a huge number of devices and objects that have very low or nonexistent processing and communication resources, coupled to a small number of high-power devices. The weakest devices, which are most ubiquitous, will not be able to authenticate themselves using cryptographic methods. This project addresses these issues using physical unclonable functions (PUFs). PUFs, and especially quantum readout PUFs, are ideally suited to the IoT setting because they allow for the authentication and identification of physical objects without requiring any crypto or storage of secret information.
Furthermore, we foresee that back-end systems will not be able to provide security and privacy via cryptographic primitives due to the sheer number of IoT devices. Our plan is to address these problems using privacy preserving database structures and algorithms with good scaling behaviour. Approximate nearest neighbour (ANN) search algorithms, which have remarkably good scaling behaviour, have recently become highly efficient, but do not yet have the right security properties and have not yet been applied to PUF data. Summarised in a nutshell, the project aims to improve the theory and practice of technologies such as PUFs and ANN search in the context of generic IoT authentication and identification scenarios.
Collaborations with Major European Organizations
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Other partners: PUCPR, Curitiba, Brasil; CNRS-STL Lille; Inserm LTSI/CHU Rennes
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Abstract: FIGTEM is a research project that involves STL-CNRS, CHU Rennes, PUC Parana, Curitiba and led by Linkmedia Ṫhis project aimed at developing natural language processing methods, including information extraction and indexing, dedicated to the clinical trial domain. The goal was to populate a formal representation of patients (via their electronic patient records) and clinical trial data in different languages (French, English, Portuguese). The main outcomes of the project was NLP tools for these 3 languages and annotated datasets made available for research purposes. It ended in May 2019.