Privacy-preserving data aggregation in Intelligent Transportation Systems

Intelligent Transportation Systems(ITS) demonstrate innovative services relating to different modes of transport and traffic management. For this, ITS rely on data collected by volunteer users in traffic. The aggregated information collected periodically offers the possibility to learn general statistics and provides ITS users with a common traffic view. For user's sensitive data, it is desired to hide individual values from other participants, but also from the ITS data aggregator, because this could disclose sensitive information. Therefore, we propose a schema for privacy-preserving aggregation based on symmetric cryptography of time-series data applicable for ITS applications.

[1]  Andreas Peter,et al.  Publicly Verifiable Private Aggregation of Time-Series Data , 2015, 2015 10th International Conference on Availability, Reliability and Security.

[2]  Marc Joye,et al.  A Scalable Scheme for Privacy-Preserving Aggregation of Time-Series Data , 2013, Financial Cryptography.

[3]  Divyakant Agrawal,et al.  Proceedings of the 2015 ACM SIGMOD International Conference on Management of Data , 2010, SIGMOD 2010.

[4]  Elaine Shi,et al.  Privacy-Preserving Aggregation of Time-Series Data , 2011, NDSS.

[5]  Ciprian Dobre,et al.  Putting the User in Control of the Intelligent Transportation System , 2016, ACISP.

[6]  Delphine Christin,et al.  Privacy in mobile participatory sensing , 2016 .

[7]  Ciprian Dobre,et al.  Secure model to share data in Intelligent Transportation Systems , 2016, 2016 18th Mediterranean Electrotechnical Conference (MELECON).

[8]  Qinghua Li,et al.  Efficient and privacy-preserving data aggregation in mobile sensing , 2012, 2012 20th IEEE International Conference on Network Protocols (ICNP).

[9]  Qinghua Li,et al.  Efficient Privacy-Preserving Stream Aggregation in Mobile Sensing with Low Aggregation Error , 2013, Privacy Enhancing Technologies.

[10]  Chi Zhang,et al.  Verifiable Privacy-Preserving Aggregation in People-Centric Urban Sensing Systems , 2013, IEEE Journal on Selected Areas in Communications.

[11]  Elaine Shi,et al.  Privacy-Preserving Stream Aggregation with Fault Tolerance , 2012, Financial Cryptography.

[12]  Florian Kerschbaum,et al.  Fault-Tolerant Privacy-Preserving Statistics , 2012, Privacy Enhancing Technologies.

[13]  Delphine Reinhardt.  Privacy in mobile participatory sensing: Current trends and future challenges , 2016, J. Syst. Softw..

[14]  Ming Li,et al.  Privacy-preserving verifiable data aggregation and analysis for cloud-assisted mobile crowdsourcing , 2016, IEEE INFOCOM 2016 - The 35th Annual IEEE International Conference on Computer Communications.

[15]  Refik Molva,et al.  Private and Dynamic Time-Series Data Aggregation with Trust Relaxation , 2014, CANS.