Artificial intelligence is a rapidly developing field of research with many practical
applications. Congruent to advances in technologies that enable big data, deep learning …

The data mining sanitization process involves converting the data by masking the sensitive
data and then releasing it to public domain. During the sanitization process, side effects …

There is incredible volume of data that is generated at exponential rate by various
organizations such as hospitals, insurance companies, banks, stock market etc. It is done by …

Data anonymization irrecoverably transforms the raw data into a protected version by
eliminating direct identifiers and removing sufficient details from indirect identifiers in order …

In the context of information systems, text sanitization techniques are used to identify and
remove sensitive data to comply with security and regulatory requirements. Even though …

Anonymization techniques based on obfuscating the quasi-identifiers by means of value
generalization hierarchies are widely used to achieve preset levels of privacy. To prevent …

Exponential trends in data generation are presenting today's organizations, economies and
governments with challenges never encountered before, especially in the field of privacy …

European Union has aggregated the current societal concerns into two seemingly
orthogonal directions: the Green Deal and the GDPR. In this paper, we begin to analyse …

With the increased use of Artificial Intelligence (AI), concerns about AI's energy consumption
are increasing as well. This paper investigates the impact of k-anonymisation and dataset …

Abstract k-anonymity is an approach for enabling privacy-preserving data publishing of
personal, sensitive data. As a result of this anonymisation process, the utility of the sanitised …