Privacy-preserving Scanpath Comparison for Pervasive Eye Tracking

Suleyman Ozdel, Efe Bozkir, Enkelejda Kasneci

Publikation: Beitrag in FachzeitschriftArtikelBegutachtung

Abstract

As eye tracking becomes pervasive with screen-based devices and head-mounted displays, privacy concerns regarding eye-tracking data have escalated. While state-of-the-art approaches for privacy-preserving eye tracking mostly involve differential privacy and empirical data manipulations, previous research has not focused on methods for scanpaths. We introduce a novel privacy-preserving scanpath comparison protocol designed for the widely used Needleman-Wunsch algorithm, a generalized version of the edit distance algorithm. Particularly, by incorporating the Paillier homomorphic encryption scheme, our protocol ensures that no private information is revealed. Furthermore, we introduce a random processing strategy and a multi-layered masking method to obfuscate the values while preserving the original order of encrypted editing operation costs. This minimizes communication overhead, requiring a single communication round for each iteration of the Needleman-Wunsch process. We demonstrate the efficiency and applicability of our protocol on three publicly available datasets with comprehensive computational performance analyses and make our source code publicly accessible.

OriginalspracheEnglisch
Aufsatznummer231
FachzeitschriftProceedings of the ACM on Human-Computer Interaction
Jahrgang8
AusgabenummerETRA
DOIs
PublikationsstatusVeröffentlicht - 28 Mai 2024

Fingerprint

Untersuchen Sie die Forschungsthemen von „Privacy-preserving Scanpath Comparison for Pervasive Eye Tracking“. Zusammen bilden sie einen einzigartigen Fingerprint.

Dieses zitieren