The spoofing attacks largely rely on the difference between human and AI image recognition. For the most part, the images Nassi and his team projected to troll the Tesla would not fool a typical human driver — in fact, some of the spoofing attacks were nearly steganographic
, relying on the differences in perception not only to make spoofing attempts successful but also to hide them from human read.
offering the video, an abstract outlining his work, and the full reference paper itself. We don’t necessarily agree with the spin Nassi puts on his work — for the most part, it looks to us like the Tesla responds pretty reasonably and well to these deliberate attempts to confuse its sensors. We do think this kind of work is important, however, as it demonstrates the need for defensive design of semi-autonomous driving systems.
Nassi and his team’s spoofing of the Model X was carried out with a human assistant holding a projector, due to drone laws in the country where the experiments were carried out. But the spoof could have also been carried out by drone, as his earlier spoofing attacks on a Mobileye driver-assistance system were.
From a security perspective, the interesting angle here is that the attacker never has to be at the scene of the attack and Does not need to leave any evidence behind — and the attacker does not need much technical expertise. A teenager with a $ 551 drone and a battery-powered projector could reasonably pull this off with no more know-how than “hey, it’d be hilarious to troll cars down at the highway, right?” The equipment does not need to be expensive or fancy — Nassi’s team used several $ – $ 551 projectors successfully, one of which was rated for only (x) resolution and lumens.