Towards a privacy-preserving hybrid radio network: Design and open challenges

Mirco Schonfeld, Martin Werner, Claudia Linnhoff-Popien, Alexander Erk

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

A large-scale system hundreds of millions of people encounter every day is radio. While this system has a tremendous reach it also is technologically outdated. Technological constraints offer great protection of listeners' privacy but prevent radio stations from implementing modern business models like personalization and mining valueable user information, at the same time. This paper describes a fully distributed system that aims at overcoming current technological constraints in interconnecting radio stations and their listeners while retaining a comparable protection of sensitive user data. Namely, a peerto-peer architecture with integrated data-mining-capabilities employing differential privacy is proposed. The system will offer personalizable radio programs to listeners and it will enable radio stations to gather valuable information about their listeners. Furthermore, this paper points out key challenges in deploying, bootstrapping and maintaining such a distributed system.

Original languageEnglish
Title of host publication2015 15th International Conference on Innovations for Community Services, I4CS 2015
EditorsChristian Erfurth, Gerald Eichler, Gerald Eichler, Jorg Roth
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781467373289
DOIs
StatePublished - 7 Oct 2015
Externally publishedYes
Event15th International Conference on Innovations for Community Services, I4CS 2015 - Nuremberg, Germany
Duration: 8 Jul 201510 Jul 2015

Publication series

Name2015 15th International Conference on Innovations for Community Services, I4CS 2015

Conference

Conference15th International Conference on Innovations for Community Services, I4CS 2015
Country/TerritoryGermany
CityNuremberg
Period8/07/1510/07/15

Keywords

  • Information-centric networking
  • content-delivery network
  • personalization
  • privacy-preserving data mining

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