Privacy preservation in big data from the communication perspective—A survey
T Wang, Z Zheng, MH Rehmani… - … Surveys & Tutorials, 2018 - ieeexplore.ieee.org
The advancement of data communication technologies promotes widespread data collection
and transmission in various application domains, thereby expanding big data significantly …
and transmission in various application domains, thereby expanding big data significantly …
A survey on privacy properties for data publishing of relational data
Recent advances in telecommunications and database systems have allowed the scientific
community to efficiently mine vast amounts of information worldwide and to extract new …
community to efficiently mine vast amounts of information worldwide and to extract new …
Pufferfish: A framework for mathematical privacy definitions
D Kifer, A Machanavajjhala - ACM Transactions on Database Systems …, 2014 - dl.acm.org
In this article, we introduce a new and general privacy framework called Pufferfish. The
Pufferfish framework can be used to create new privacy definitions that are customized to the …
Pufferfish framework can be used to create new privacy definitions that are customized to the …
Sok: differential privacies
D Desfontaines, B Pejó - arXiv preprint arXiv:1906.01337, 2019 - arxiv.org
Shortly after it was first introduced in 2006, differential privacy became the flagship data
privacy definition. Since then, numerous variants and extensions were proposed to adapt it …
privacy definition. Since then, numerous variants and extensions were proposed to adapt it …
A rigorous and customizable framework for privacy
D Kifer, A Machanavajjhala - Proceedings of the 31st ACM SIGMOD …, 2012 - dl.acm.org
In this paper we introduce a new and general privacy framework called Pufferfish. The
Pufferfish framework can be used to create new privacy definitions that are customized to the …
Pufferfish framework can be used to create new privacy definitions that are customized to the …
Bayesian and frequentist semantics for common variations of differential privacy: Applications to the 2020 census
The purpose of this paper is to guide interpretation of the semantic privacy guarantees for
some of the major variations of differential privacy, which include pure, approximate, R\'enyi …
some of the major variations of differential privacy, which include pure, approximate, R\'enyi …
Tunable measures for information leakage and applications to privacy-utility tradeoffs
We introduce a tunable measure for information leakage called maximal-leakage. This
measure quantifies the maximal gain of an adversary in inferring any (potentially random) …
measure quantifies the maximal gain of an adversary in inferring any (potentially random) …
Pointwise maximal leakage
We introduce a privacy measure called pointwise maximal leakage, generalizing the pre-
existing notion of maximal leakage, which quantifies the amount of information leaking about …
existing notion of maximal leakage, which quantifies the amount of information leaking about …
Exponential random graph estimation under differential privacy
W Lu, G Miklau - Proceedings of the 20th ACM SIGKDD international …, 2014 - dl.acm.org
The effective analysis of social networks and graph-structured data is often limited by the
privacy concerns of individuals whose data make up these networks. Differential privacy …
privacy concerns of individuals whose data make up these networks. Differential privacy …
Structure and Sensitivity in Differential Privacy: Comparing K-Norm Mechanisms
J Awan, A Slavković - Journal of the American Statistical …, 2021 - Taylor & Francis
Differential privacy (DP) provides a framework for provable privacy protection against
arbitrary adversaries, while allowing the release of summary statistics and synthetic data …
arbitrary adversaries, while allowing the release of summary statistics and synthetic data …