A survey on the densest subgraph problem and its variants
The Densest Subgraph Problem requires us to find, in a given graph, a subset of vertices
whose induced subgraph maximizes a measure of density. The problem has received a …
whose induced subgraph maximizes a measure of density. The problem has received a …
Privacy preserving social network data publication
JH Abawajy, MIH Ninggal… - … communications surveys & …, 2016 - ieeexplore.ieee.org
The introduction of online social networks (OSN) has transformed the way people connect
and interact with each other as well as share information. OSN have led to a tremendous …
and interact with each other as well as share information. OSN have led to a tremendous …
Towards practical differential privacy for SQL queries
Differential privacy promises to enable general data analytics while protecting individual
privacy, but existing differential privacy mechanisms do not support the wide variety of …
privacy, but existing differential privacy mechanisms do not support the wide variety of …
The complexity of differential privacy
S Vadhan - Tutorials on the Foundations of Cryptography …, 2017 - Springer
Differential privacy is a theoretical framework for ensuring the privacy of individual-level data
when performing statistical analysis of privacy-sensitive datasets. This tutorial provides an …
when performing statistical analysis of privacy-sensitive datasets. This tutorial provides an …
Differentially private data publishing and analysis: A survey
Differential privacy is an essential and prevalent privacy model that has been widely
explored in recent decades. This survey provides a comprehensive and structured overview …
explored in recent decades. This survey provides a comprehensive and structured overview …
Linkteller: Recovering private edges from graph neural networks via influence analysis
Graph structured data have enabled several successful applications such as
recommendation systems and traffic prediction, given the rich node features and edges …
recommendation systems and traffic prediction, given the rich node features and edges …
Analyzing graphs with node differential privacy
SP Kasiviswanathan, K Nissim… - Theory of Cryptography …, 2013 - Springer
We develop algorithms for the private analysis of network data that provide accurate
analysis of realistic networks while satisfying stronger privacy guarantees than those of …
analysis of realistic networks while satisfying stronger privacy guarantees than those of …
Applications of differential privacy in social network analysis: A survey
Differential privacy provides strong privacy preservation guarantee in information sharing.
As social network analysis has been enjoying many applications, it opens a new arena for …
As social network analysis has been enjoying many applications, it opens a new arena for …
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 …
Publishing graph degree distribution with node differential privacy
Graph data publishing under node-differential privacy (node-DP) is challenging due to the
huge sensitivity of queries. However, since a node in graph data oftentimes represents a …
huge sensitivity of queries. However, since a node in graph data oftentimes represents a …