Data Analysis Systems in IoE Environments for Managing Privacy and Data Protection: Pseudonymity, De-Anonymization and the Right to Be Forgotten

Authors

  • Merugu Anand Kumar, Dr. S. Gowri Author

DOI:

https://doi.org/10.48047/t4gbmd21

Keywords:

Privacy, Anonymization, Data Analytics, Big Data.

Abstract

One of the most pressing concerns surrounding Big Data is protecting individuals' privacy, as processing 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 to protect large data analytics systems from re-identification risks, this article lays forth a methodology for anonymization

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References

Podda, Emanuela. "Big data analysis systems in IoE environments for managing privacy and data protection: pseudonymity, de-anonymization and the right to be forgotten." (2023).

Bolognini, Luca, and Camilla Bistolfi. "Pseudonymization and impacts of Big (personal/anonymous) Data processing in the transition from the Directive 95/46/EC to the new EU General Data Protection Regulation." Computer law & security review 33, no. 2 (2017): 171-181.

Tudor, Valentin, Magnus Almgren, and Marina Papatriantafilou. "The influence of dataset characteristics on privacy preserving methods in the advanced metering infrastructure." Computers & Security 76 (2018): 178-196.

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Published

2024-12-10

How to Cite

Data Analysis Systems in IoE Environments for Managing Privacy and Data Protection: Pseudonymity, De-Anonymization and the Right to Be Forgotten (Merugu Anand Kumar, Dr. S. Gowri , Trans.). (2024). Cuestiones De Fisioterapia, 53(03), 497-508. https://doi.org/10.48047/t4gbmd21