Organizations and enterprises search for ways to exploit the vast amount of data that is produced by citizens, sensors, devices and administrative processes. Capitalizing on the produced data should be done responsibly by preventing, mitigating and managing undesired side effects such as violation of …

Machine learning models use high dimensional feature spaces to map their inputs to the corresponding class labels. However, these features often do not have a one-to-one correspondence with physical concepts understandable by humans, which hinders the ability to provide a meaningful explanation for the …

There are many good reasons to use synthetic data instead of real data for research purposes. These reasons may range from the business sensitiveness of real data to increased cost of collecting real data in accordance with GDPR requirements. In this paper, we elaborate upon the potentials of the Large …

Securing information systems and assets within smart shipping environments is of utmost importance. In practice, however, securing smart shipping is a difficult and tedious task because smart shipping environments are highly dynamic, distributed, and loosely coupled, which cause having large threat/attack …

A core principle of privacy protection is to minimize the amount of personal data in data sets to the level needed for the intended usage. The rapid growth of data and data-driven applications demands for using efficient software tools to minimize personal data to the needed level. However, applying …

ChatGPT is rapidly gaining interest and attracts many researchers, practitioners and users due to its availability, potentials and capabilities. Nevertheless, there are several voices and studies that point out the flaws of ChatGPT such as its hallucinations, factually incorrect statements, and potential …

Machine learning models have been an inevitable tool for analyzing medical images by radiologists. These models provide important information about the contents of these images using extracted radiomic features. However, the dimensionality of the feature space can cause reduction in the accuracy of prediction, …

Data reusability has become a distinct characteristic of scientific, commercial, and administrative practices nowadays. However, an unlimited and careless reuse of data may lead to privacy breaches and unfair impacts on individuals and vulnerable groups. Data content adaption is a key aspect of preserving …

Privacy is a comprehensive notion which is hard to grasp for the layman. To make the privacy notion tangible, creating transparency about privacy practices is an important necessity. Transparency about privacy practices is traditionally (sought to be) established via providing privacy policies and privacy …

Some public organisations struggle to meet the Open Data requirements fully because their data often have sensitive (personal) information, are of low quality, or have interoperability issues in terms of format and semantics. These restrictions quite often hold for justice domain datasets. In order to …