Related papers: Passive Triangulation Attack on ORide
In this paper, a delay-angle information spoofing (DAIS) strategy is proposed for location-privacy enhancement. By shifting the location-relevant delays and angles without the aid of channel state information (CSI) at the transmitter, the…
Today people increasingly have the opportunity to opt-in to "usage-based" automotive insurance programs for reducing insurance premiums. In these programs, participants install devices in their vehicles that monitor their driving behavior,…
In order to mitigate the distance reduction attack in Ultra-Wide Band (UWB) ranging, this paper proposes a secure ranging scheme based on a random time-hopping mechanism without redundant signaling overhead. Additionally, a secure ranging…
Many Intelligent Transportation Systems (ITS) applications require strong privacy guarantees for both users and their data. Homomorphic encryption (HE) enables computation directly on encrypted messages and thus offers a compelling approach…
As the most promising application in VANETs, the vehicular announcement allows vehicles to send announcement messages about road conditions to other vehicles far away. The security requirements of reliability and privacy in the vehicular…
We introduce a deep learning framework able to deal with strong privacy constraints. Based on collaborative learning, differential privacy and homomorphic encryption, the proposed approach advances state-of-the-art of private deep learning…
Hybrid reflective intelligent surfaces (HRISs) can support localization in sixth-generation (6G) networks thanks to their ability to generate narrow beams and at the same time receive and process locally the impinging signals. In this…
In this paper we propose a novel protocol that allows suppliers and grid operators to collect users' aggregate metering data in a secure and privacy-preserving manner. We use secure multiparty computation to ensure privacy protection. In…
Location-based alerts have gained increasing popularity in recent years, whether in the context of healthcare (e.g., COVID-19 contact tracing), marketing (e.g., location-based advertising), or public safety. However, serious privacy…
Reversible data hiding (RDH) has been extensively studied in the field of information security. In our previous work [1], an explicit implementation approaching the rate-distortion bound of RDH has been proposed. However, there are two…
In transportation networks, users typically choose routes in a decentralized and self-interested manner to minimize their individual travel costs, which, in practice, often results in inefficient overall outcomes for society. As a result,…
This paper presents an optimisation-based approach for an obstacle avoidance problem within an autonomous vehicle racing context. Our control regime leverages online reachability analysis and sensor data to compute the maximal safe…
We propose a novel hierarchical online intrusion detection system (HOIDS) for supervisory control and data acquisition (SCADA) networks based on machine learning algorithms. By utilizing the server-client topology while keeping clients…
Location information is critical to a wide-variety of navigation and tracking applications. Today, GPS is the de-facto outdoor localization system but has been shown to be vulnerable to signal spoofing attacks. Inertial Navigation Systems…
Objectives: We introduce a new method for reducing crime in hot spots and across cities through ridge estimation. In doing so, our goal is to explore the application of density ridges to hot spots and patrol optimization, and to contribute…
Crowdsourcing plays an essential role in the Internet of Things (IoT) for data collection, where a group of workers is equipped with Internet-connected geolocated devices to collect sensor data for marketing or research purpose. In this…
The on-demand mobility market, including ridesharing, is becoming increasingly important with e-hailing fares growing at a rate of approximately 130% per annum since 2013. By increasing utilization of existing vehicles and empty seats,…
The current COVID-19 pandemic highlights the utility of contact tracing, when combined with case isolation and social distancing, as an important tool for mitigating the spread of a disease [1]. Contact tracing provides a mechanism of…
Distributed optimization is manifesting great potential in multiple fields, e.g., machine learning, control, and resource allocation. Existing decentralized optimization algorithms require sharing explicit state information among the…
An increasing amount of mobility data is being collected every day by different means, such as mobile applications or crowd-sensing campaigns. This data is sometimes published after the application of simple anonymization techniques (e.g.,…