Artikel in Tagungsband INPROC-2024-03

Bibliograph.
Daten
Fieschi, Andrea; Hirmer, Pascal; Agrawal, Sachin; Stach, Christoph; Mitschang, Bernhard: HySAAD - A Hybrid Selection Approach for Anonymization by Design in the Automotive Domain.
In: Renso, Chiara (Hrsg); Sakr, Mahmoud (Hrsg); Aref, Walid G (Hrsg); Song, Ashley (Hrsg); Long, Cheng (Hrsg): Proceedings of the 25th IEEE International Conference on Mobile Data Management (MDM 2024).
Universität Stuttgart, Fakultät Informatik, Elektrotechnik und Informationstechnik.
S. 203-210, englisch.
Los Alamitos, Washington, Tokyo: IEEE Computer Society Conference Publishing Services, Juni 2024.
ISBN: 979-8-3503-7455-1; ISSN: 2375-0324; DOI: 10.1109/MDM61037.2024.00044.
Artikel in Tagungsband (Konferenz-Beitrag).
CR-Klassif.K.4.1 (Computers and Society Public Policy Issues)
Keywordsanonymization; connected vehicles; privacy protection; metrics
Kurzfassung

The increasing connectivity and data exchange between vehicles and the cloud have led to growing privacy concerns. To keep on gaining product insights through data collection while guaranteeing privacy protection, an anonymization-by-design approach should be used. A rising number of anonymization methods, not limited to the automotive domain, can be found in the literature and practice. The developers need support to select the suitable anonymization technique. To this end, we make the following two contributions: 1) We apply our knowledge from the automotive domain to outline the usage of qualitative metrics for anonymization techniques assessment; 2) We introduce HySAAD, a hybrid selection approach for anonymization by design that leverages this groundwork by recommending appropriate anonymization techniques for each mobile data analytics use case based on both, qualitative (i.e., ßoft") metrics and quantitative (i.e., "hard") metrics. Using a real-world use case from the automotive, we demonstrate the applicability and effectiveness of HySAAD.

CopyrightCopyright © 2024 IEEE by The Institute of Electrical and Electronics Engineers, Inc. All rights reserved.
KontaktSenden Sie eine E-Mail an <andrea.fieschi@ipvs.uni-stuttgart.de>.
Abteilung(en)Universität Stuttgart, Institut für Parallele und Verteilte Systeme, Anwendersoftware
Projekt(e)SofDCar
Eingabedatum16. Juli 2024
   Publ. Informatik