Saved in:
Bibliographic Details
Main Authors: Filipczuk, Dorota, Gerding, Enrico H., Konstantinidis, George
Format: Preprint
Published: 2024
Subjects:
Online Access:https://arxiv.org/abs/2403.11361
Tags: Add Tag
No Tags, Be the first to tag this record!
_version_ 1866916163638788096
author Filipczuk, Dorota
Gerding, Enrico H.
Konstantinidis, George
author_facet Filipczuk, Dorota
Gerding, Enrico H.
Konstantinidis, George
contents Through legislation and technical advances users gain more control over how their data is processed, and they expect online services to respect their privacy choices and preferences. However, data may be processed for many different purposes by several layers of algorithms that create complex data workflows. To date, there is no existing approach to automatically satisfy fine-grained privacy constraints of a user in a way which optimises the service provider's gains from processing. In this article, we propose a solution to this problem by modelling a data flow as a graph. User constraints and processing purposes are pairs of vertices which need to be disconnected in this graph. In general, this problem is NP-hard, thus, we propose several heuristics and algorithms. We discuss the optimality versus efficiency of our algorithms and evaluate them using synthetically generated data. On the practical side, our algorithms can provide nearly optimal solutions for tens of constraints and graphs of thousands of nodes, in a few seconds.
format Preprint
id arxiv_https___arxiv_org_abs_2403_11361
institution arXiv
publishDate 2024
record_format arxiv
spellingShingle Graph Theory for Consent Management: A New Approach for Complex Data Flows
Filipczuk, Dorota
Gerding, Enrico H.
Konstantinidis, George
Databases
Through legislation and technical advances users gain more control over how their data is processed, and they expect online services to respect their privacy choices and preferences. However, data may be processed for many different purposes by several layers of algorithms that create complex data workflows. To date, there is no existing approach to automatically satisfy fine-grained privacy constraints of a user in a way which optimises the service provider's gains from processing. In this article, we propose a solution to this problem by modelling a data flow as a graph. User constraints and processing purposes are pairs of vertices which need to be disconnected in this graph. In general, this problem is NP-hard, thus, we propose several heuristics and algorithms. We discuss the optimality versus efficiency of our algorithms and evaluate them using synthetically generated data. On the practical side, our algorithms can provide nearly optimal solutions for tens of constraints and graphs of thousands of nodes, in a few seconds.
title Graph Theory for Consent Management: A New Approach for Complex Data Flows
topic Databases
url https://arxiv.org/abs/2403.11361