GPS-dependent applications are ever-increasing and it is becoming an attractive target for hackers.
The GPS spoofing attacks are critical as the navigation systems are actively used by
billions of drivers on the road and play a key role in autonomous vehicles.
Four Step GPS spoofing Attack
Researchers derived a four-step attack method to show how the hackers can manipulate the road navigation systems.
A Portable GPS Spoofer worth 223 US Dollars, that includes HackRF, a Raspberry Pi, a portable power source and an antenna.
For measurement, they derived two possible methods that attackers can manipulate the GPS signals.
Placing spoofer in the victim’s car
Researchers started testing by placing the spoofer in the victim’s car and by having XIAOMI MIX2 with Android 8.0 in the dashboard as a GPS device. With this attack, the take over time from the trunk is 48 seconds and from the backseat 35 seconds.
Two different cars
By placing the spoofer and GPS device in two different cars the take over time 41.2 seconds and the effective spoofing range is 40–50 meters.
“To further examine the sustainability of the signal lock-in, we fix the location of the spoofer’s car and let the victim’s car drive in circles (about 10 mph) while keeping
a distance for 15 meters. After driving non-stop for 15 minutes, we did not observe any disconnections, which confirms the sustainability.”
Researchers derived a stealthy algorithm that crafts the GPS inputs to the target device such that the triggered navigation instruction and displayed routes on the map remain consistent with the physical road network.
The algorithm implemented for real-world scenarios, according to the driving tests on the road confirm the attack feasibility.
“We conduct a user study to demonstrate the attack feasibility with human drivers in the loop. The results provide key insights into how common driving habits make users vulnerable.”
“Researchers said our attacks is more suitable to run in the cities where the road networks are dense. We use the maps of Manhattan(NY) and Boston(MA). To examine the attack performance we randomly select 600 real-world taxi trips. Our attack success rate is (95%).”