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Anonymization Techniques for Behavioral Biometric Data: A Survey

Hanisch, Simon 1,2; Arias-Cabarcos, Patricia 1; Parra-Arnau, Javier; Strufe, Thorsten ORCID iD icon 1
1 Kompetenzzentrum für angewandte Sicherheitstechnologie (KASTEL), Karlsruher Institut für Technologie (KIT)
2 Technische Universität Dresden (TU Dresden)

Abstract (englisch):

Our behavior—the way we talk, walk, act, or think—is unique and can be used as a biometric trait. It also correlates with sensitive attributes such as emotions and health conditions. With more and more behavior tracking techniques (e.g., fitness trackers, mixed reality) entering our everyday lives, more of our behavior is captured and processed. Hence, techniques to protect individuals’ privacy against unwanted inferences are required before such data is processed. To consolidate knowledge in this area, we are the first to systematically review suggested anonymization techniques for behavioral biometric data. We taxonomize and compare existing solutions regarding privacy goals, conceptual operation, advantages, and limitations. Our categorization allows for the comparison of anonymization techniques across different behavioral biometric traits. We review anonymization techniques for the behavioral biometric traits of voice, gait, hand motions, eye gaze, heartbeat (ECG), and brain activity (EEG). Our analysis shows that some behavioral traits (e.g., voice) have received much attention, while others (e.g., eye gaze, brain activity) are mostly neglected. ... mehr


Verlagsausgabe §
DOI: 10.5445/IR/1000182613
Veröffentlicht am 25.06.2025
Originalveröffentlichung
DOI: 10.1145/3729418
Scopus
Zitationen: 2
Web of Science
Zitationen: 2
Dimensions
Zitationen: 2
Cover der Publikation
Zugehörige Institution(en) am KIT Kompetenzzentrum für angewandte Sicherheitstechnologie (KASTEL)
Publikationstyp Zeitschriftenaufsatz
Publikationsdatum 12.06.2025
Sprache Englisch
Identifikator ISSN: 0360-0300, 1557-7341
KITopen-ID: 1000182613
HGF-Programm 46.23.01 (POF IV, LK 01) Methods for Engineering Secure Systems
Erschienen in ACM Computing Surveys
Verlag Association for Computing Machinery (ACM)
Band 57
Vorab online veröffentlicht am 18.04.2025
Nachgewiesen in Web of Science
Scopus
OpenAlex
Dimensions
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