The Automatic Dependant Surveillance-Broadcast (ADS-B) message scheme was designed without any authentication or encryption of messages in place. It is therefore easily possible to attack it, e.g., by injecting spoofed messages or modifying the transmitted Global Navigation Satellite System (GNSS) coordinates. In order to verify the integrity of the received information, various methods have been suggested, such as multilateration, the use of Kalman filters, group certification, and many others. However, solutions based on modifications of the standard may be difficult and too slow to be implemented due to legal and regulatory issues. A vantage far less explored is the location verification using public sensor data. In this paper, we propose LoVe, a lightweight message verification approach that uses a geospatial indexing scheme to evaluate the trustworthiness of publicly deployed sensors and the ADS-B messages they receive. With LoVe, new messages can be evaluated with respect to the plausibility of their reported coordinates in a location privacy-preserving manner, while using a datadriven and lightweight approach. By testing our approach on two open datasets, we show that LoVe achieves very low false positive rates (between 0 and 0.001 06) and very low false negative rates (between 0.000 65 and 0.003 34) while providing a real-time compatible approach that scales well even with a large sensor set. Compared to currently existing approaches, LoVe neither requires a large number of sensors, nor for messages to be recorded by as many sensors as possible simultaneously in order to verify location claims. Furthermore, it can be directly applied to currently deployed systems thus being backward compatible.

The use of public Wi-Fi networks can reveal sensitive data to both operators and bystanders. A VPN can prevent this. However, a machine that initiates a connection to a VPN server might already leak sensitive data before the VPN tunnel is fully established. Furthermore, it might not be immediately possible to establish a VPN connection if the network requires authentication via a captive portal, thus increasing the leakage potential. In this paper we examine both issues. For that, we analyse the behaviour of native and third-party VPN clients on various platforms, and introduce a new method called selective VPN bypassing to avoid captive portal deadlocks.