Work

Efficient Privacy-Preserved Processing of Multimodal Data for Vehicular Traffic Analysis

Year: 2023

Type: conference-paper

Abstract: We estimate vehicular traffic states from multimodal data collected by single-loop detectors while preserving the privacy of the individual vehicles contributing to the data.To this end, we propose a novel hybrid differential privacy (DP) approach that utilizes minimal randomization to preserve privacy by taking advantage of the relevant traffic state dynamics and the concept of DP sensitivity.Through theoretical analysis and experiments with real-world data, we show that the proposed approach significantly outperforms the related baseline nonprivate and private approaches in terms of accuracy and privacy preservation.

DOI: 10.14722/vehiclesec.2023.23052

Authors: Meisam Mohammady, Reza Arablouei

Institutions: Iowa State University, Commonwealth Scientific and Industrial Research Organisation, Data61

Language: English

Topic: Privacy-Preserving Technologies in Data

Subfield: Artificial Intelligence

Field: Computer Science

Domain: Physical Sciences

SDGs: Sustainable cities and communities, Industry, innovation and infrastructure

Open Access status: gold

OpenAlex ID: W4321473583

FWCI:

Cites: 32

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Related to: 10