Federated learning is a decentralized machine learning technique that aggregates partial models trained by a set of clients on their own private data to obtain a global model....

Our society is being shaped in a non-negligible way by the technological advances of recent years, especially in information and communications technologies (ICTs). The...

Information technology allows us to generate, store, and process huge quantities of data. Search engines, satellites, sensor networks, scientists, security agencies,...

Informational self-determination refers to the right or ability of individuals to exercise personal control over the collection, use and disclosure of their personal data by...

This article describes an emergent logic of accumulation in the networked sphere, ‘surveillance capitalism,’ and considers its implications for ‘information civilization.’ The...

The rise of “Big Data” analytics in the private sector poses new challenges for privacy advocates. Through its reliance on existing data and predictive analysis to create...

Anonymization for privacy-preserving data publishing, also known as statistical disclosure control (SDC), can be viewed under the lens of the permutation model. According to...

This webinar, which took place on 6 July 2021, focused on the interplay between legal data and data science. The webinar, entitled ‘Legal Materials as Big Data: (algo)Rithms to...

This webinar, which took place on 10 November 2020, was aimed at exploring the theme of data protection and intellectual property issues in platforms. The first speaker was...

The Multi-Task Faces (MTF) dataset consists of cropped human faces for classification tasks or other research purposes. Each image in the dataset is labelled according to four...

Privlib is a Python software package to manage privacy risk and discrimination in tabular and sequential data. It comprises methods to assess privacy risk (PRUDEnce) and...

Artificial intelligence (AI) is being deployed in missions that are increasingly critical for human life. To build trust in AI and avoid an algorithm-based authoritarian...

An ever-increasing number of decisions affecting our lives are made by algorithms. For this reason, algorithmic transparency is becoming a pressing need: automated decisions...

The role of decisions made by machine learning algorithms in our lives is ever increasing. In reaction to this phenomenon, the European General Data Protection Regulation...

This python library implements the discrimination discovery and prevention method proposed in the paper: “A methodology for direct and indirect discrimination prevention in...

This method provides a Privacy Risk Assessment on CDR data, aggregated through the presence vectors used by the Sociometer.

This method provides a Privacy Risk Assessment on mobility data, in terms of trajectories or aggregation of trajectories, i.e., locations with frequency of visit and locations...

This method is a fast and flexible approach to estimate privacy risk in human mobility data. The idea is to train classifiers to capture the relation between individual...

4th SoBigData++ Awareness Panel Webinar Programme Decentralized anonymization of mobility data Speaker: Josep Domingo-Ferrer (Universitat Rovira i Virgili, Catalonia)...

These tutorials show how to use the already implemented libraries for the anonymization and antidiscrimination of data sets: - Anonymization library:...