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.

Self-Sovereign Identity can be considered as the most significant paradigm shift, surpassing the more established centralised and federated approaches that have shaped identity management in the past decades.

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.

Published by Big Data Value Association (BDVA)

Chapter 11 in book “Challenges in Cybersecurity and Privacy – the European Research Landscape”, ISBN: 978-87-7022-088-0

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

ARES '17 Proceedings of the 12th International Conference on Availability, Reliability and Security Article No. 89

ERCIM News 109