This month, advertising giant WPP will send unusual corporate training videos to tens of thousands of employees worldwide. A presenter will speak in the recipient’s language and address them by name, while explaining some basic concepts in artificial intelligence. The videos themselves will be powerful demonstrations of what AI can do: The face, and the words it speaks, will be synthesized by software.

WPP doesn’t bill them as such, but its synthetic training videos might be called deepfakes, a loose term applied to images or videos generated using AI that look real. Read More

Autonomous vehicles can be fooled by “phantom” images displayed on a road, wall or sign, causing them to unexpectedly brake or veer off course and making them vulnerable to attackers, Israeli researchers said.

Semi- and fully-autonomous cars perceive and respond to two-dimensional projections as real objects, according to researchers from the Ben-Gurion University of the Negev. Read More

The absence of deployed vehicular communication systems, which prevents the advanced driving assistance systems (ADASs) and autopilots of semi/fully autonomous cars to validate their virtual perception regarding the physical environment surrounding the car with a third party, has been exploited in various attacks suggested by researchers. Since the application of these attacks comes with a cost (exposure of the attacker’s identity), the delicate exposure vs. application balance has held, and attacks of this kind have not yet been encountered in the wild. In this paper, we investigate a new perceptual challenge that causes the ADASs and autopilots of semi/fully autonomous to consider depthless objects (phantoms) as real. We show how attackers can exploit this perceptual challenge to apply phantom attacks and change the abovementioned balance, without the need to physically approach the attack scene, by projecting a phantom via a drone equipped with a portable projector or by presenting a phantom on a hacked digital billboard that faces the Internet and is located near roads. We show that the car industry has not considered this type of attack by demonstrating the attack on today’s most advanced ADAS and autopilot technologies: Mobileye 630 PRO and the Tesla Model X, HW 2.5; our experiments show that when presented with various phantoms, a car’s ADAS or autopilot considers the phantoms as real objects, causing these systems to trigger the brakes, steer into the lane of oncoming traffic, and issue notifications about fake road signs. In order to mitigate this attack, we present a model that analyzes a detected object’s context, surface, and reflected light, which is capable of detecting phantoms with 0.99 AUC. Finally, we explain why the deployment of vehicular communication systems might reduce attackers’ opportunities to apply phantom attacks but won’t eliminate them. Read More

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