HDTcrypt: Compression and encryption of RDF datasets

Article type: Research Article

Authors: Fernández, Javier D.^{a; b; *} | Kirrane, Sabrina^a | Polleres, Axel^{a; b} | Steyskal, Simon^{a; c}

Affiliations: [a] Institute for Information Business, Vienna University of Economics and Business, Austria. E-mails: javier.fernandez@wu.ac.at, sabrina.kirrane@wu.ac.at, axel.polleres@wu.ac.at, simon.steyskal@wu.ac.at | [b] Complexity Science Hub Vienna, Austria | [c] CT RDA BAM CON-AT, Siemens AG, Austria. E-mail: simon.steyskal@siemens.com

Correspondence: [*] Corresponding author. E-mail: javier.fernandez@wu.ac.at.

Abstract: The publication and interchange of RDF datasets online has experienced significant growth in recent years, promoted by different but complementary efforts, such as Linked Open Data, the Web of Things and RDF stream processing systems. However, the current Linked Data infrastructure does not cater for the storage and exchange of sensitive or private data. On the one hand, data publishers need means to limit access to confidential data (e.g. health, financial, personal, or other sensitive data). On the other hand, the infrastructure needs to compress RDF graphs in a manner that minimises the amount of data that is both stored and transferred over the wire. In this paper, we demonstrate how HDT – a compressed serialization format for RDF – can be extended to cater for supporting encryption. We propose a number of different graph partitioning strategies and discuss the benefits and tradeoffs of each approach.

Keywords: RDF, HDT, compression, encryption, linked data protection

DOI: 10.3233/SW-180335

Journal: Semantic Web, vol. 11, no. 2, pp. 337-359, 2020