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Journal Articles PeerJ Computer Science Year : 2022

Privacy-preserving solution for vehicle parking services complying with EU legislation

Petr Dzurenda
  • Function : Author
Florian Jacques
  • Function : Author
Manon Knockaert
  • Function : Author
Lukas Malina
  • Function : Author
Raimundas Matulevicius
  • Function : Author
Qiang Tang
  • Function : Author
Aimilia Tasidou

Abstract

Today, many modern cities adopt online smart parking services as best practices. Citizens can easily access these services using their smartphones or the infotainment panels in their cars. These services’ primary objective is to give drivers the ability to quickly identify free parking slots, which should reduce parking time, save fuel, and relieve traffic in urban areas. However, the privacy offered by these services should be comparable to that of the standard paper-based parking solutions offered by parking ticket machines. On the other hand, a privacy-preserving smart parking service’s design may raise a number of issues, including how to prevent double or multiple uses of parking tickets, how to prevent user tracking and profiling, how to revoke malicious users, how to handle data statistics without violating users’ privacy, and how to comply with regulations like the General Data Protection Regulation (GDPR). In this article, we present multidisciplinary research on a comprehensive vehicle parking system that protects users’ privacy. The research includes a range of topics, from the examination of regulatory compliance to the design of privacy-preserving parking registration and vehicle parking services to the implementation of privacy-preserving parking data processing features for data analysts. We provide a security analysis of our concept as well as several experimental results.
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Dates and versions

hal-03997331 , version 1 (20-02-2023)

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Petr Dzurenda, Florian Jacques, Manon Knockaert, Maryline Laurent, Lukas Malina, et al.. Privacy-preserving solution for vehicle parking services complying with EU legislation. PeerJ Computer Science, 2022, 8, pp.e1165. ⟨10.7717/peerj-cs.1165⟩. ⟨hal-03997331⟩
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