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A Differentially Private Hybrid Approach to Traffic Monitoring

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  • Rogério V.M. Rocha, Universidade Estadual de Campinas
  • ,
  • Pedro P. Libório, Universidade Estadual de Campinas
  • ,
  • Harsh Kupwade Patil
  • ,
  • Diego F. Aranha

In recent years, privacy research has been gaining ground in vehicular communication technologies. Collecting data from connected vehicles presents a range of opportunities for industry and government to perform data analytics. Although many researchers have explored some privacy solutions for vehicular communications, the conditions to deploy them are still maturing, especially when it comes to privacy for sensitive data aggregation analysis. In this work, we propose a hybrid solution combining the original differential privacy framework with an instance-based additive noise technique. The results show that for typical instances we obtain a significant reduction in outliers. As far as we know, our paper is the first detailed experimental evaluation of differentially private techniques applied to traffic monitoring. The validation of the proposed solution was performed through extensive simulations in typical traffic scenarios using real data.

Original languageEnglish
Title of host publicationApplied Cryptography and Network Security - ACNS 2021
EditorsKazue Sako, Nils Ole Tippenhauer
Number of pages24
Place of publicationCham
Publication year2021
ISBN (print)978-3-030-78374-7
ISBN (Electronic)978-3-030-78375-4
Publication statusPublished - 2021
Event19th International Conference on Applied Cryptography and Network Security, ACNS 2021 - Virtual, Online
Duration: 21 Jun 202124 Jun 2021


Conference19th International Conference on Applied Cryptography and Network Security, ACNS 2021
ByVirtual, Online
SeriesLecture Notes in Computer Science

    Research areas

  • Differential privacy, Hybrid approach, Intelligent Transportation Systems (ITS), Smooth sensitivity

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