SOMAR: privacy-preserving SOcial media advertising architecture: or: how not to leave your personal data around

Publikationstyp
Conference Paper
Date Issued
2017-10-30
Sprache
English
Author(s)
Becker, Daniela  
Guajardo, Jorge  
Zimmermann, Karl-Heinz  
Institut
Eingebettete Systeme E-13  
TORE-URI
http://hdl.handle.net/11420/3543
Start Page
21
End Page
30
Citation
WPES 2017 - Proceedings of the 2017 Workshop on Privacy in the Electronic Society, co-located with CCS 2017: 21-30 (2017-10-30)
Contribution to Conference
16th ACM Workshop on Privacy in the Electronic Society, WPES 2017  
Publisher DOI
10.1145/3139550.3139563
Scopus ID
2-s2.0-85043392789
Publisher
ACM
Social media marketing has emerged as a new tool for brands to reach certain target groups. While the use of platforms like Instagram and Facebook has created a multi-billion dollar business, it has also multiplied the amount of sensitive data that is being collected. The associated risks for the end user in terms of data privacy have grown accordingly and most users are unaware of what happens to their data in the background. We propose a novel privacy-preserving social media advertising architecture called SOMAR, which offers a solution that is beneficial to all parties: user privacy is protected and advertisers receive sufficient statistical data, such that all marketing services can be provided in a privacyfriendly manner without sacrificing functionality. Additionally, all computed statistics are equipped with proofs of correctness such that the currently trust-based relationship between brands and social media marketers is replaced by cryptographic verifiability.
DDC Class
600: Technik