Work

Privacy Modeling and Enhancement Methodology for JCAS-Enabled Railway Applications

Year: 2024

Type: conference-paper

Abstract: In this paper, we present a new risk-based methodology for assessing privacy impacts in joint communication and sensing (JCAS)-based systems, with a focus on providingprivacy-enhancing measures for 6G applications. To illustrate the methodology’s applicability, we explore a railway use case where a JCAS system monitors level crossings for obstacles. Additionally, we offer a short demonstration of how the methodology applies to this use case scenario.

Source: Zenodo (CERN European Organization for Nuclear Research)

DOI: 10.5281/zenodo.14161649

Author: Barkhausen Institute

Language: English

Topic: Privacy-Preserving Technologies in Data

Subfield: Artificial Intelligence

Field: Computer Science

Domain: Physical Sciences

SDG: Industry, innovation and infrastructure

Open Access status: green

OpenAlex ID: W6949592677

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