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Privacy-Protecting Techniques for Behavioral Data: A Survey

Hanisch, Simon; Arias-Cabarcos, Patricia; Parra-Arnau, Javier; Strufe, Thorsten

Abstract (englisch):

Our behavior (the way we talk, walk, or think) is unique and can be used as a biometric trait. It also correlates with sensitive attributes like emotions. Hence, techniques to protect individuals privacy against unwanted inferences are required. To consolidate knowledge in this area, we systematically reviewed applicable anonymization techniques. We taxonomize and compare existing solutions regarding privacy goals, conceptual operation, advantages, and limitations. Our analysis shows that some behavioral traits (e.g., voice) have received much attention, while others (e.g., eye-gaze, brainwaves) are mostly neglected. We also find that the evaluation methodology of behavioral anonymization techniques can be further improved.

Volltext §
DOI: 10.5445/IR/1000139989
Veröffentlicht am 12.11.2021
Cover der Publikation
Zugehörige Institution(en) am KIT Kompetenzzentrum für angewandte Sicherheitstechnologie (KASTEL)
Publikationstyp Forschungsbericht/Preprint
Publikationsdatum 09.09.2021
Sprache Englisch
Identifikator KITopen-ID: 1000139989
HGF-Programm 46.23.01 (POF IV, LK 01) Methods for Engineering Secure Systems
Verlag arxiv
Schlagwörter Informatik, Sicherheit, Privacy, Security, CS, behavioral data, de-identification
Nachgewiesen in arXiv
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