Related papers: Trust but Verify: Cryptographic Data Privacy for M…
Machine Learning on Big Data gets more and more attention in various fields. Even so privacy-preserving techniques become more important, even necessary due to legal regulations such as the General Data Protection Regulation (GDPR). On the…
In MaaS (Mobility as a Service), means of transport are virtualized in mobility resources and provided to users using the Internet. From a legal perspective, this model of ITS (Intelligent Transport System) raises several concerns with…
Navigation is one of the most popular cloud computing services. But in virtually all cloud-based navigation systems, the client must reveal her location and destination to the cloud service provider in order to learn the fastest route. In…
Smart cities often rely on technological innovation to improve citizens' safety and quality of life. This paper presents a novel smart mobility system that aims to facilitate people accessing public mobility while preserving their privacy.…
Intelligent infrastructure will critically rely on the dense instrumentation of sensors and actuators that constantly transmit streaming data to cloud-based analytics for real-time monitoring. For example, driverless cars communicate…
Transformer models have revolutionized AI, enabling applications like content generation and sentiment analysis. However, their use in Machine Learning as a Service (MLaaS) raises significant privacy concerns, as centralized servers process…
The evolution of Big Data in large-scale Internet-of-Vehicles has brought forward unprecedented opportunities for a unified management of the transportation sector, and for devising smart Intelligent Transportation Systems. Nevertheless,…
Urban transportation is being transformed by mobility-on-demand (MoD) systems. One of the goals of MoD systems is to provide personalized transportation services to passengers. This process is facilitated by a centralized operator that…
Digitisation is often viewed as beneficial to a user. Whereas traditionally, people would physically have to identify to a service, pay for a ticket in cash, or go into a library to access a book, people can now achieve all of this through…
With low-cost computing devices, improved sensor technology, and the proliferation of data-driven algorithms, we have more data than we know what to do with. In transportation, we are seeing a surge in spatiotemporal data collection. At the…
Data-driven methodologies offer many exciting upsides, but they also introduce new challenges, particularly in the realm of user privacy. Specifically, the way data is collected can pose privacy risks to end users. In many routing services,…
As a significant business paradigm, many online information platforms have emerged to satisfy society's needs for person-specific data, where a service provider collects raw data from data contributors, and then offers value-added data…
Network-level adversaries have developed increasingly sophisticated techniques to surveil and control users' network traffic. In this paper, we exploit our observation that many encrypted protocol connections are no longer tied to device IP…
The widespread adoption of continuously connected smartphones and tablets developed the usage of mobile applications, among which many use location to provide geolocated services. These services provide new prospects for users: getting…
We consider a fully-decentralized scenario in which no central trusted entity exists and all clients are honest-but-curious. The state-of-the-art approaches to this problem often rely on cryptographic protocols, such as multiparty…
Private data generated by edge devices -- from smart phones to automotive electronics -- are highly informative when aggregated but can be damaging when mishandled. A variety of solutions are being explored but have not yet won the public's…
The outbreak of coronavirus disease 2019 (covid-19) is imposing a severe worldwide lock-down. Contact tracing based on smartphones' applications (apps) has emerged as a possible solution to trace contagions and enforce a more sustainable…
Cryptographic primitives are essential for constructing privacy-preserving communication mechanisms. There are situations in which two parties that do not know each other need to exchange sensitive information on the Internet. Trust…
The ubiquitous presence of mobile communication devices and the continuous development of mo- bile data applications, which results in high level of mobile devices' activity and exchanged data, often transparent to the user, makes privacy…
Blockchain has the potential to render the transaction of information more secure and transparent. Nowadays, transportation data are shared across multiple entities using heterogeneous mediums, from paper collected data to smartphone. Most…