TU Darmstadt / ULB / TUbiblio

Privacy by Design: Analysis of Capacitive Proximity Sensing as System of Choice for Driver Vehicle Interfaces

Frank, Sebastian and Kuijper, Arjan (2020):
Privacy by Design: Analysis of Capacitive Proximity Sensing as System of Choice for Driver Vehicle Interfaces.
In: HCI International 2020 – Late Breaking Papers: Digital Human Modeling and Ergonomics, Mobility and Intelligent Environments, pp. 51-66,
Springer, 22nd HCI International Conference, 19.-24.07.2020, ISBN 978-3-030-59986-7,
DOI: 10.1007/978-3-030-59987-4_5,
[Conference or Workshop Item]

Abstract

Data collection is beneficial. Therefore, automotive manufacturers start including data collection services. At the same time, manufacturers install cameras for human machine interfaces in vehicles. But those systems may disclose further information than needed for gesture recognition. Thus, they may cause privacy issues. The law (GDPR) enforces privacy by default and design. Research often states that capacitive proximity sensing is better to serve privacy by design than cameras. Furthermore, it is unclear if customers value privacy preserving features. Nonetheless, manufacturers value the customer’s voice. Therefore, several vehicular human machine interface systems, with camera or capacitive proximity sensing, are analyzed. Especially concerning gesture recognition, capacitive proximity sensing systems provide similar features like camera-based systems. The analysis is based on the GDPR privacy definition. Due to the analysis, it is revealed that capacitive proximity sensing systems have less privacy concerns causing features. Subsequently, three hypotheses are formulated to capture the customer’s voice. Due to analysis results, it is questionable if gesture recognition systems, which utilize cameras, are compliant with privacy by design. Especially since well-known systems like capacitive proximity sensing are available. A survey concerning the hypotheses will give further insights in future work.

Item Type: Conference or Workshop Item
Erschienen: 2020
Creators: Frank, Sebastian and Kuijper, Arjan
Title: Privacy by Design: Analysis of Capacitive Proximity Sensing as System of Choice for Driver Vehicle Interfaces
Language: English
Abstract:

Data collection is beneficial. Therefore, automotive manufacturers start including data collection services. At the same time, manufacturers install cameras for human machine interfaces in vehicles. But those systems may disclose further information than needed for gesture recognition. Thus, they may cause privacy issues. The law (GDPR) enforces privacy by default and design. Research often states that capacitive proximity sensing is better to serve privacy by design than cameras. Furthermore, it is unclear if customers value privacy preserving features. Nonetheless, manufacturers value the customer’s voice. Therefore, several vehicular human machine interface systems, with camera or capacitive proximity sensing, are analyzed. Especially concerning gesture recognition, capacitive proximity sensing systems provide similar features like camera-based systems. The analysis is based on the GDPR privacy definition. Due to the analysis, it is revealed that capacitive proximity sensing systems have less privacy concerns causing features. Subsequently, three hypotheses are formulated to capture the customer’s voice. Due to analysis results, it is questionable if gesture recognition systems, which utilize cameras, are compliant with privacy by design. Especially since well-known systems like capacitive proximity sensing are available. A survey concerning the hypotheses will give further insights in future work.

Title of Book: HCI International 2020 – Late Breaking Papers: Digital Human Modeling and Ergonomics, Mobility and Intelligent Environments
Publisher: Springer
ISBN: 978-3-030-59986-7
Uncontrolled Keywords: Capacitive proximity sensing, Advanced driver assistance systems (ADAS), Privacy enhancing technologies
Divisions: 20 Department of Computer Science
20 Department of Computer Science > Interactive Graphics Systems
20 Department of Computer Science > Mathematical and Applied Visual Computing
Event Title: 22nd HCI International Conference
Event Dates: 19.-24.07.2020
Date Deposited: 02 Dec 2020 12:34
DOI: 10.1007/978-3-030-59987-4_5
Additional Information:

Part of the Lecture Notes in Computer Science book series (LNCS, volume 12429)

Export:
Suche nach Titel in: TUfind oder in Google
Send an inquiry Send an inquiry

Options (only for editors)
Show editorial Details Show editorial Details