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.

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.

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.

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.

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

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

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