Final master thesis supervision: Building a Python library for anonymizing sensitive data
Final master thesis supervision, International University Menéndez Pelayo (UIMP) and University of Cantabria (UC), 2023
Title of the master thesis supervised: “Building a Python library for anonymizing sensitive data”.
Author: Esmeralda Madrazo Quintana.
Directors: Álvaro López García and Judith Sáinz-Pardo Díaz.
Abstract: Technologies that handle large amounts of data have experienced rapid growth in recent years, thanks mainly to the easy availability of large volumes of data (big data). Problems arise when trying to maintain the balance between privacy and preserving as much information as possible. The dilemma of privacy preservation is further intensified when handling databases containing, for example, clinical patient data. The objective of this master’s thesis is to address privacy issues in data science by exploring and implementing the most common anonymization techniques. More specifically, we intend to implement a Python library with the most popular anonymization models, more specifically k-anonymity, l-diversity and t-closeness, as well as offer some performance analysis techniques for its optimal implementation.
Link: https://repositorio.unican.es/xmlui/handle/10902/30791