An Anonymization Library for Rapid and Diverse Anonymization of Brazilian Personal Data

Abstract

The prevalence of personal data in the hands of large companies highlights the necessity for robust regulatory frameworks. The General Data Protection Law (LGPD) seeks to standardize data usage, emphasizing minimal ownership and, when needed, anonymization in line with regulations. The absence of a specific tool for anonymizing Brazilian personal data remains a significant challenge. The lack of a dedicated tool for anonymizing Brazilian personal data poses a hurdle in achieving LGPD compliance. This study proposes the development of a library tailored to anonymize personal data, considering the unique aspects of Brazilian regulations. The goal is to create an efficient and secure library for removing identifiable information from documents, aligning with the LGPD. Furthermore, the results obtained from the implementation and testing of the developed library provide significant contributions to the data privacy community. The successful integration of support for various document formats such as .PDF, .DOCX, and .XLSX, coupled with the ability to anonymize text strings, demonstrates the versatility and practicality of the library. Notably, the performance tests reveal promising outcomes, showcasing the effectiveness of each function and regular expression employed. These results not only validate the functionality of the library but also underscore its potential in aiding individuals and organizations in adhering to data protection regulations.