Big Data Anonymization Requirements vs Privacy Models

Josep Domingo-Ferrer

2018

Abstract

The big data explosion opens unprecedented analysis and inference possibilities that may even enable modeling the world and forecasting its evolution with great accuracy. The dark side of such a data bounty is that it complicates the preservation of individual privacy: a substantial part of big data is obtained from the digital track of our activity. We focus here on the privacy of subjects on whom big data are collected. Unless anonymization approaches are found that are suitable for big data, the following extreme positions will become more and more common: nihilists, who claim that privacy is dead in the big data world, and fundamentalists, who want privacy even at the cost of sacrificing big data analysis. In this article we identify requirements that should be satisfied by privacy models to be applicable to big data. We then examine how well the two main privacy models (k-anonymity and ε-differential privacy) satisfy those requirements. Neither model is entirely satisfactory, although k-anonymity seems more amenable to big data protection. Finally, we highlight connections between the previous two privacy models and other privacy models that might result in synergies between them in order to tackle big data: the principles underlying all those models are deniability and permutation. Future research attempting to adapt the current privacy models for big data and/or design new models will have to adhere to those two underlying principles. As a side result, the above inter-model connections allow gauging what is the actual protection afforded by differential privacy when ε is not sufficiently small.

Paper Citation

in Harvard Style

Domingo-Ferrer J. (2018). Big Data Anonymization Requirements vs Privacy Models.In Proceedings of the 15th International Joint Conference on e-Business and Telecommunications - Volume 1: SECRYPT, ISBN 978-989-758-319-3, pages 305-312. DOI: 10.5220/0006830003050312

in Bibtex Style

@conference{secrypt18,
author={Josep Domingo-Ferrer},
title={Big Data Anonymization Requirements vs Privacy Models},
booktitle={Proceedings of the 15th International Joint Conference on e-Business and Telecommunications - Volume 1: SECRYPT,},
year={2018},
pages={305-312},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0006830003050312},
isbn={978-989-758-319-3},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 15th International Joint Conference on e-Business and Telecommunications - Volume 1: SECRYPT,
TI - Big Data Anonymization Requirements vs Privacy Models
SN - 978-989-758-319-3
AU - Domingo-Ferrer J.
PY - 2018
SP - 305
EP - 312
DO - 10.5220/0006830003050312