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Configurable Per-Query Data Minimization for Privacy-Compliant Web APIs

Authors :
Pallas, Frank
Hartmann, David
Heinrich, Paul
Kipke, Josefine
Grünewald, Elias
Publication Year :
2022

Abstract

The purpose of regulatory data minimization obligations is to limit personal data to the absolute minimum necessary for a given context. Beyond the initial data collection, storage, and processing, data minimization is also required for subsequent data releases, as it is the case when data are provided using query-capable Web APIs. Data-providing Web APIs, however, typically lack sophisticated data minimization features, leaving the task open to manual and all too often missing implementations. In this paper, we address the problem of data minimization for data-providing, query-capable Web APIs. Based on a careful analysis of functional and non-functional requirements, we introduce Janus, an easy-to-use, highly configurable solution for implementing legally compliant data minimization in GraphQL Web APIs. Janus provides a rich set of information reduction functionalities that can be configured for different client roles accessing the API. We present a technical proof-of-concept along with experimental measurements that indicate reasonable overheads. Janus is thus a practical solution for implementing GraphQL APIs in line with the regulatory principle of data minimization.<br />Comment: Preprint version (2022-03-18) This version of the contribution has been accepted for publication at the 22nd International Conference on Web Engineering (ICWE 2022), Bari, Italy

Details

Database :
arXiv
Publication Type :
Report
Accession number :
edsarx.2203.09903
Document Type :
Working Paper
Full Text :
https://doi.org/10.1145/3493369.3493601