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Unmanned aerial vehicles (UAVs) are widely deployed in air navigation, where numerous applications use them for safety-of-life and positioning, navigation, and timing tasks. Consequently, GPS spoofing attacks are more and more frequent. The aim of this work is to enhance GPS systems of UAVs, by providing the ability of detecting and preventing spoofing attacks. The proposed solution is based on a multilayer perceptron neural network, which processes the flight parameters and the GPS signals to generate alarms signalling GPS spoofing attacks. The obtained accuracy lies between 83.23% for TEXBAT dataset and 99.93% for MAVLINK dataset. This work was supported in part by the Catalan Government, through the program 2017-SGR-962 and the RIS3CAT DRAC project 001-P-001723, and by the EPFL, Switzerland.

Numerous studies have shown that Operating System (OS) noise is one of the reasons for significant performance degradation in clustered architectures. Although many studies examine the OS noise for High Performance Computing, especially in multi-processor/core systems, most of them focus on 2- or 4-core systems. In this study, we analyze sources of OS noise on a massive multithreading processor, the Sun UltraSPARC T1.We compare results, measured in Linux and Solaris, with the results provided by a low-overhead runtime environment that introduces almost no overhead in applications’ execution time. Our results show that the overhead introduced by the OS timer interrupt in Linux and Solaris depends on the particular core and hardware context in which the application is running. This overhead is up to 30% when the application is executed on the same hardware context as the timer interrupt handler, and up to 10% when the application and the timer interrupt handler run on different contexts but on the same core. We detect no overhead when the benchmark and the timer interrupt handler run on different cores of the processor.