Towards Querying in Decentralized Environments with Privacy-Preserving Aggregation

Ruben Taelman, Simon Steyskal, Sabrina Kirrane

Publication: Chapter in book/Conference proceedingContribution to conference proceedings

Abstract

The Web is a ubiquitous economic, educational, and collaborativespace, however, it also serves as a haven for personal information harvesting. Ex-isting decentralised Web-based ecosystems, such as Solid, aim to combat personaldata exploitation on the Web by enabling individuals to manage their data in thepersonal data store of their choice. Since personal data in these decentralisedecosystems are distributed across many sources, there is a need for techniques tosupport efficient privacy-preserving query execution over personal data stores.Towards this end, in this position paper we present a framework for efficient pri-vacy preserving federated querying, and highlight open research challenges andopportunities. The overarching goal being to provide a means to position futureresearch into privacy-preserving querying within decentralised environments.
Original languageEnglish
Title of host publicationJoint Proceedings of Workshops AI4LEGAL2020, NLIWOD, PROFILES 2020, QuWeDa 2020 and SEMIFORM2020 Colocated with the 19th International Semantic Web Conference (ISWC 2020)
Editors Manolis Koubarakis, Harith Alani, Grigoris Antoniou, Kalina Bontcheva, John Breslin, Diego Collarana, Elena Demidova, Stefan Dietze, Simon Gottschalk, Guido Governatori, Aidan Hogan, Freddy Lecue, Elena Montiel Ponsoda, Axel-Cyrille Ngonga Ngomo, Sofia Pinto, Muhammad Saleem, Raphael Troncy, Eleni Tsalapati, Ricardo Usbeck, Ruben Verborgh
Place of PublicationAthens - Online Event
Pages135 - 148
Publication statusPublished - 2020

Austrian Classification of Fields of Science and Technology (ÖFOS)

  • 102001 Artificial intelligence
  • 102015 Information systems
  • 102 not use (legacy)
  • 502050 Business informatics
  • 505002 Data protection

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