Abstract

Location spoofing has long been an outstanding issue among mobile devices. By manipulating the devices’ GPS values via location spoofing applications, attackers can easily give false reporting on their current locations. Such spoofing behavior can cause serious troubles and even put other people in danger. Many researches are being done in identifying spoofing behavior by making use of the relationship between the location of the device and the signal strength of its connected Wi-Fi network. They give good results in detection on long distance travels while fall short in recognizing spoofing behavior in close range. We address this issue and propose an identification methodology to predict the motion status of a mobile device by taking advantage of the short-range property of the Bluetooth wireless network. We carry out inquiry scans using the Bluetooth discovery functionality available in most mobile devices to collect information of the devices nearby to learn about the surrounding environment, which can then be used to verify the genuineness of the GPS data. Experiment results show that our method can evidently distinguish between various motion status of the device by making statistical analysis on the distribution of appearance of the discovered devices.