Create, Read, Update and Delete operations (CRUD) are a well-established abstraction to model data access in software systems of different architectures. Most system requirements, generated during the specification phase, will be realized by combining ...

This paper explores the critical aspects of behavioural modelling for sustainability in smart homes, emphasising the integration of advanced technologies to enhance energy efficiency, convenience, security, and overall quality of life. Smart homes ...

Artificial intelligence systems such as Large Language Models (LLM) derive their knowledge from large datasets. Systems like ChatGPT therefore rely on shared data to train on. For companies, releasing data to the public domain requires anonymization as ...

In parallel with the rapid development of Information and Communication technologies and the digitization of information in every aspect of daily life, the enforcement of the GDPR, in May 2018, brought significant changes to the processes that ...

In this paper, we present further contributions to the field of privacy-preserving and explainable data analysis applied to tabular datasets. Our approach defines a comprehensive optimization criterion that balances the key aspects of data privacy, ...

In the rapidly evolving digital healthcare landscape, the imperative for robust, flexible, and scalable data protection solutions has never been more critical. The advent of sophisticated cyber threats, coupled with the increasing complexity of ...

The main goal of the EU GDPR is to protect personal data of individuals within the EU. This is expressed in several rights and, among them, in this work we focus on the Right to Erasure, more commonly known as the Right to Be Forgotten (RtBF).

There is ...

Vehicle-to-Everything (V2X) technologies have been recently introduced to provide enhanced connectivity between the different smart grid segments as well as Electric Vehicles (EVs). The EVs draw power to the grid and may be used as an energy flexibility ...

Time is an often recurring quasi-identifying attribute in many datasets. Anonymizing such datasets requires generalizing the time attribute(s) in the dataset. Examples are start dates and durations, which are traditionally generalized leading to ...

Data processors increasingly rely on external data sources to improve strategic or operational decision taking. Data owners can facilitate this by releasing datasets directly to data processors or doing so indirectly via data spaces. As data processors ...