Abstract In this paper we propose Privacy-preserving User-data Bookkeeping & Analytics (PUBA), a building block destined to enable the implementation of business models (e.g., targeted advertising) and regulations (e.g., fraud detection) requiring user-data analysis in a privacy-preserving way. In PUBA, users keep an unlinkable but authenticated cryptographic logbook containing their historic data on their device. This logbook can only be updated by the operator while its content is not revealed. Users can take part in a privacy-preserving analytics computation, where it is ensured that their logbook is up-to-date and authentic while the potentially secret analytics function is verified to be privacy-friendly. Taking constrained devices into account, users may also outsource analytic computations (to a potentially malicious proxy not colluding with the operator).We model our novel building block in the Universal Composability framework and provide a practical protocol instantiation. To demonstrate the flexibility of PUBA, we sketch instantiations of privacy-preserving fraud detection and targeted advertising, although it could be used in many more scenarios, e.g. data analytics for multi-modal transportation systems. We implemented our bookkeeping protocols and an exemplary outsourced analytics computation based on logistic regression using the MP-SPDZ MPC framework. Performance evaluations using a smartphone as user device and more powerful hardware for operator and proxy suggest that PUBA for smaller logbooks can indeed be practical.

Abstract Electronic toll collection (ETC) is widely used all over the world not only to finance our road infrastructures, but also to realize advanced features like congestion management and pollution reduction by means of dynamic pricing. Unfortunately, existing systems rely on user identification and allow tracing a user’s movements. Several abuses of this personalized location data have already become public. In view of the planned Europeanwide interoperable tolling system EETS and the new EU General Data Protection Regulation, location privacy becomes of particular importance. In this paper, we propose a flexible security model and crypto protocol framework designed for privacy-preserving toll collection in the most dominant setting, i.e., Dedicated Short Range Communication (DSRC) ETC. A major challenge in designing the framework at hand was to combine provable security and practicality, where the latter includes practical performance figures and a suitable treatment of real-world issues, like broken onboard units etc. To the best of our knowledge, our work is the first in the DSRC setting with a rigorous security model and proof and arguably the most comprehensive formal treatment of ETC security and privacy overall. Additionally, we provide a prototypical implementation on realistic hardware which already features fairly practical performance figures. An interaction between an onboard unit and a road-side unit is estimated to take less than a second allowing for toll collection at full speed assuming one road-side unit per lane.