Data Analysis Systems in IoE Environments for Managing Privacy and Data Protection: Pseudonymity, De-Anonymization and the Right to Be Forgotten
Year: 2025
Type: article
Abstract: One of the most pressing concerns surrounding Big Data is protecting individuals' privacy, asprocessing massive amounts of data might lead to the exposure of private information. Actually,re-identification via privacy attacks is still possible, even with anonymised data. In order toprotect large data analytics systems from re-identification risks, this article lays forth amethodology for anonymization. You may employ anonymization methods and models at twophases of this framework, which is based on anonymization policies: during the ETL process andbefore exporting the statistical findings of data analytics. The second step is to assess thelikelihood of data re-identification and, if needed, raise the anonymity level. Although this paperpresents a general framework, Ophidia was used as a case study to demonstrate how it wasimplemented.
Source: Cuestiones de Fisioterapia
DOI: 10.48047/b23v4479
Author: 1Merugu Anand Kumar, Dr. S. Gowri
Language: English
Subfield: Artificial Intelligence
Field: Computer Science
Domain: Physical Sciences
Open Access status: hybrid
OpenAlex ID: W4408161320