Preserving data privacy in Machine Learning pipelines with Federated Learning

FAME's project blog
The feature extraction capabilities of Machine Learning (ML) models have led to their wide adoption in a large variety of sectors: from anomaly detection for machinery, to user clustering and behavioral prediction, market trends predictions, or the analysis of text, sound, and image data.

Leveraging Large Language Models for Financial Predictions

FAME project blog
In the world of finance, where every decision can have significant ramifications, the possibility of predicting market movements is invaluable. Traditionally, analysts have relied on a combination of data analysis, market trends, and expert insights to make informed predictions.

FAME: Federated Decentralized Trusted Data Marketplace for Embedded Finance

IEEE
Due to its multivariate and multipurpose use and reuse, data’s worth is dramatically increasing, leading to an era characterized by the generation of data marketplaces towards accessing, selling, sharing, and trading data and data assets.

CyberSec4Europe - Securing and Preserving Privacy Sharing Health Data

ERCIM News
In the context of EU Horizon 2020 CyberSec4Europe project the medical data exchange demonstrator creates a trusted ecosystem for sharing medical data in a secure and privacy preserving manner.

Current Hot Topics in Data Protection

Big Data Value Association
The BDVA position paper Current Hot Topics in Data Protection summarizes the latest and emerging challenges and developments in the field, with a focus on the European Union: "The new paper introduces pr

KRAKEN - Brokerage and Market Platform for Personal data

'Fighting Cyber-Crime'
The EU Horizon 2020 KRAKEN project is dedicated to building a trusted and secure personal data platform enabling exchange and analytics of personal data.

LEPS – Leveraging eID in the Private Sector

Chapter in book “Challenges in Cybersecurity and Privacy - the European Research Landscape” by River Publishers. ISBN: 9788770220880 doi: https://doi.org/10.13052/rp-9788770220873 https://www.riverpublishers.com/research_details.php?book_id=711