Why we need better defenses against VR cyberattacks

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I remember the first time I tried on a VR headset. It was the first Oculus Rift, and I nearly fainted after experiencing an intense but visually clumsy VR roller-coaster. But that was a decade ago, and the experience has gotten a lot smoother and more realistic since.That impressive level of immersiveness could be a problem, though: it makes us particularly vulnerable to cyberattacks in VR.

I justpublished a storyabout a new kind of security vulnerability discovered by researchers at the University of Chicago. Inspired by the Christoper Nolan movieInception, the attack allows hackers to create an app that injects malicious code into the Meta Quest VR system. Then it launches a clone of the home screen and apps that looks identical to the user's original screen. Once inside, attackers are able to see, record, and modify everything the person does with the VR headset, tracking voice, motion, gestures, keystrokes, browsing activity, and even interactions with other people in real time. New fear = unlocked.

The findings are pretty mind-bending, in part because the researchers' unsuspecting test subjects had absolutely no idea they were under attack.You can read more about it in my story here.

It's shocking to see how fragile and unsecure these VR systems are, especially considering that Meta's Quest headset is the most popular such product on the market, used by millions of people.

But perhaps more unsettling is how attacks like this can happen without our noticing, and can warp our sense of reality. Past studies have shown how quickly people start treating things in AR or VR as real, says Franzi Roesner, an associate professor of computer science at the University of Washington, who studies security and privacy but was not part of the study. Even in very basic virtual environments, people start stepping around objects as if they were really there.

VR has the potential to put misinformation, deception and other problematic content on steroids because it exploits people's brains, and deceives them physiologically and subconsciously, says Roesner: The immersion is really powerful."

And because VR technology is relatively new, people aren't vigilantly looking out for security flaws or traps while using it. To test how stealthy the inception attack was, the University of Chicago researchers recruited 27 volunteer VR experts to experience it. One of the participants was Jasmine Lu, a computer science PhD researcher at the University of Chicago. She says she has been using, studying, and working with VR systems regularly since 2017. Despite that, the attack took her and almost all the other participants by surprise.

As far as I could tell, there was not any difference except a bit of a slower loading time-things that I think most people would just translate as small glitches in the system," says Lu.

One of the fundamental issues people may have to deal with in using VR is whether they can trust what they're seeing, says Roesner.

Lu agrees. She says that with online browsers, we have been trained to recognize what looks legitimate and what doesn't, but with VR, we simply haven't. People do not know what an attack looks like.

This is related to a growing problem we're seeing with the rise of generative AI, and even with text, audio, and video: it isnotoriously difficult to distinguish real from AI-generated content. The inception attack shows that we need to think of VR as another dimension in a world where it's getting increasingly difficult to know what's real and what's not.

As more people use these systems, and more products enter the market, the onus is on the tech sector to develop ways to make them more secure and trustworthy.

The good news? While VR technologies are commercially available, they're not all that widely used, says Roesner. So there's time to start beefing up defenses now.

Now read the rest of The AlgorithmDeeper Learning

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In the summer of 2021, OpenAI quietly shuttered its robotics team, announcing that progress was being stifled by a lack of data necessary to train robots in how to move and reason using artificial intelligence. Now three of OpenAI's early research scientists say the startup they spun off in 2017, called Covariant, has solved that problem and unveiled a system that combines the reasoning skills of large language models with the physical dexterity of an advanced robot.

Multimodal prompting:The new model, called RFM-1, was trained on years of data collected from Covariant's small fleet of item-picking robots that customers like Crate & Barrel and Bonprix use in warehouses around the world, as well as words and videos from the internet. Users can prompt the model using five different types of input: text, images, video, robot instructions, and measurements. The company hopes the system will become more capable and efficient as it's deployed in the real world.Read more from James O'Donnell here.

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