at Google ScholarTitle data
Schönfeld, Mirco ; Werner, Martin ; Linnhoff-Popien, Claudia ; Erk, Alexander:
Towards a Privacy-Preserving Hybrid Radio Network : Design and Open Challenges.
In: Roth, Jörg ; Eichler, Gerald ; Erfurth, Christian
(ed.):
15th International Conference on Innovations for Community Services (I4CS 2015). -
Piscataway, NJ
: IEEE
,
2015
. - pp. 71-76
ISBN 978-1-4673-7327-2
DOI: https://doi.org/10.1109/I4CS.2015.7294488
Abstract in another language
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 While this "system" has a tremendous reach it also is technologically outdated.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 peer-to-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.
Further data
| Item Type: | Article in a book |
|---|---|
| Refereed: | Yes |
| Institutions of the University: | Faculties > Faculty of Languages and Literature Faculties > Faculty of Languages and Literature > Juniorprofessur Datenmodellierung und interdisziplinäre Wissensgenerierung Faculties > Faculty of Languages and Literature > Juniorprofessur Datenmodellierung und interdisziplinäre Wissensgenerierung > Juniorprofessur Datenmodellierung und interdisziplinäre Wissensgenerierung - Juniorprof. Dr. Mirco Schönfeld Faculties |
| Result of work at the UBT: | No |
| DDC Subjects: | 000 Computer Science, information, general works > 004 Computer science |
| Date Deposited: | 18 Nov 2021 10:57 |
| Last Modified: | 18 Nov 2021 10:57 |
| URI: | https://eref.uni-bayreuth.de/id/eprint/67891 |