If you were paranoid about digital tracking before, you might want to think twice about reading any further.

New research out of Germany’s Karlsruhe Institute of Technology found that the types of Wi-Fi routers we all have in our homes come with a major privacy vulnerability that can be used to identify any human body that comes within their range.

The study, flagged by Gizmodo, used machine learning systems to identify individuals with an accuracy rate of 99.5 percent. To do so, the researchers exploited a vulnerability in a process known as beamforming feedback information (BFI), which was introduced to allow routers to focus Wi-Fi signals on connected devices, as opposed to the older approach, which is to blanket an entire area in coverage.

While BFI is great for network connectivity, it has a major downsides for privacy. For starters, devices connected to a router using beamforming need to send constant feedback in order to be found. As routers send out and receive network feedback, the signal is inevitably impacted by real world factors like pets, walls, and people.

That gap, between the signals routers expect to receive and the distorted feedback they actually get, allowed researchers to extrapolate the identities of 161 individual participants based on BFI data which inadvertently mapped their physical characteristics. Even when individuals changed their gait or carried objects like backpacks and crates, the system registered an accuracy rate between 50 to 60 percent, the KIT team wrote.

“This works similar to a normal camera, the difference being that in our case, radio waves instead of light waves are used for the recognition,” study coauthors Thorsten Strufe said in a press release.

Making matters worse is the fact that this data is basically wide open for anyone to grab — not only is that feedback data unencrypted, it can also be accessed without ever connecting directly to the router.

“We have shown robust identity inference with common-of-the-shelf hardware which is already in widespread adoption in many homes and public areas,” the team wrote in their paper. “With this hardware making its way into millions of homes, the privacy concerns are severe.”

The KIT findings contrast to other Wi-Fi tracking systems, like one developed by researchers at the Sapienza University of Rome. That method, called “WhoFi,” uses channel state information, which is much harder to access on consumer hardware, but can still identify people through walls with an alarmingly high accuracy rate.

That WhoFi study made a point to highlight the anonymity factor: the idea that the sensing system can detect people’s presence, but not identify them. The KIT team refutes that framing outright, arguing that Wi-Fi-sensing technology poses major privacy risks regardless.

“While there maybe legitimate use-cases, we explicitly consider identity inference via Wi-Fi sensing a privacy attack,” they write. “This view reflects the serious risks associated with the ubiquity of Wi-Fi networks, their ability to sense through walls and in non-line-of-sight scenarios, and the fact that this would likely happen without explicit consent.”

While more research will be needed, the researchers don’t mince words about the implications of their initial findings. In their conclusion, the KIT team writes that regulators and companies moving to standardize Wi-Fi sensing should “strongly consider adding effective privacy protection,” or else “abandon beamforming entirely.”

More on surveillance: Town Councilmember Goes Berzerk at Surveillance Camera Ban, Threatens to Outlaw Virtually All Modern Technology

The post Random Standard Wi-Fi Routers Can Scan Your Body to Identify Exactly Who You Are, Alarming New Research Finds appeared first on Futurism.

Imagine this scenario: your algorithm has pulled up a background YouTube video, or maybe a podcast. Unbeknownst to you, hackers have embedded inaudible sounds in it, designed to hijack your smart speaker or phone’s AI assistant — meaning the cybercriminals can now access your private photos, bank accounts, or any other personal information you’ve hooked up to your AI system.

It sounds like an also-ran episode of “Black Mirror,” but it’s exactly what researchers have shown is possible in new research being presented this week at the IEEE Symposium on Security and Privacy.

Basically, a team of researchers in China and Singapore found that they can construct “adversarial audio,” completely undetectable to the human ear, that tricks voice AI models into doing things they shouldn’t. Then it’s a breeze to hide it in innocent-sounding audio — a song, a movie, or anything else that unsuspecting targets might play in the background — and lay in wait for users to accidentally compromise their digital lives.

“It takes just half an hour to train this signal, and then, because this signal is context-agnostic, you can use it to attack the target model whenever you want, no matter what the user says,” lead author Meng Chen, a PhD candidate at China’s Zhejiang University, told IEEE Spectrum of the work. “These single-point defenses struggle to resist our attack because we found it’s very hard for these models to distinguish the normal user intent and our adversary attack.”

One catch, at least for now: the technique required the hackers to have access to the full weights of the AI model they’re targeting, meaning they were only able to attack open source models. But because many commercial AI systems are built on open source models, that meant that their exploit was effective against mainstream products by Microsoft and Mistral.

Mistral didn’t respond to IEEE‘s request for comment, but Microsoft issued a statement that should probably give anyone pause before connecting any important information whatsoever to one of the company’s voice AI models.

“We appreciate the researchers’ work to advance understanding of this type of technique,” it read. “This study evaluates model resilience through controlled, direct interactions with the model itself, which helps inform our approach to building model resiliency. In practice, AI models are often integrated into user applications, and we offer developers tools and guidance they can use to implement additional layers of protection that help safeguard users.”

More on AI: Researchers Alarmed by AI That Can Self-Replicate Into Another Machine

The post Hackers Find That Inaudible Sounds Hidden in Podcasts or Random Videos Can Hijack Your AI Voice Chatbot appeared first on Futurism.

Like data centers, automatic license plate readers (ALPRs) are incredibly unpopular with voters around the US. Plenty of local politicians are taking the hint, choosing to cancel controversial surveillance contracts with the granddad of ALPR companies, Flock Safety.

In the tiny town of Bandera, Texas, however, one petty tyrant on the city council took personal offense after his fellow politicians voted 3-2 to immediately end their contract with Flock earlier this month. After voting, the dissenting councilmember, identified by 404 Media as Jeff Flowers, immediately went on the offensive, threatening to outlaw virtually all forms of modern technology and take the town “back to 1880.”

In a statement shared by the town newspaper the Bandera Bulletin, Flowers addressed the roughly 900 residents who call the town home.

“For months, I have listened to the outcry regarding [ALPR] technology,” he scathed. “I have seen the eyerolls, and I’ve even been met with ‘Nazi rhetoric,’ the dangerous claim that believing in accountability and community safety is somehow equivalent to totalitarianism. Comparing a neighbor’s desire for a safe street to a dark chapter of history is a classic case of comparing apples to oranges; it is a distraction used to avoid the reality of the threats our town faces today.”

“Since the Council has decided we are the ‘Free State of Bandera,’ a place where the ‘rights’ of a car thief or human trafficker to remain anonymous apparently outweigh the right of a resident to protect their property and the safety of their family, then we must go all the way,” Flowers continued his rant.

“To ensure our historic County Seat becomes the most ‘traditional’ sanctuary in Texas, I have requested… a total ban on all cellular and GPS-capable devices for all operations within city limits,” the councilman raged. “If we are to be truly ‘private,’ we must leave our smartphones at the city line.”

Continuing his childish crashout, Flowers also proposed a ban on all commercial and residential security cameras, as well as a “total total termination of all internet services and electronic record-keeping.”

“We are going back to 1880, paper ledgers and cash only,” he seethed.

Back in February, Flowers moderated a town hall meeting exclusively meant to discuss the Flock contract, which brought eight ALPRs into the one-horse town. During another February meeting, Flowers accused opponents of the private surveillance company of having something to hide, saying “I believe personally that guilty people act defensively.”

“If you don’t have anything to hide, then it shouldn’t be a problem,” he carried on. “I also believe when you are in a public space, your privacy kind of goes out the window because you are in essence in a public place.”

More on surveillance: Man Trapped in Dystopian Nightmare Thanks to AI Surveillance Cameras Flagging His Every Move

The post Town Councilmember Goes Berzerk at Surveillance Camera Ban, Threatens to Outlaw Virtually All Modern Technology appeared first on Futurism.

Researchers in Japan have succeeded in measuring the temperature inside living cells with high precision using a new class of biocompatible quantum nanosensor – something that has been difficult to do until now even. If improved, the nanosensor could be used to characterize a wide range of biological phenomena and so help in disease diagnosis, they say.

Recent years have seen the advent of a new generation of nanoscale quantum sensors that can detect the tiny magnetic fields of biological systems. Some of these sensors rely on photons and others on electrons or spin defects – typically diamond specially engineered with nitrogen–vacancy (NV) defects. This material is made by removing two carbon atoms from the diamond lattice and replacing one with a nitrogen atom. The other “hole” is left empty, thereby creating a vacancy or defect. The spin state of the defect is influenced by the local magnetic field that can be “read out” from the way it fluoresces.

While a powerful tool, and biocompatible, this type of quantum sensor does suffer from certain limits. For one, it can be structurally inhomogeneous, which affects how it detects temperature and other physical or chemical parameters inside biological cells.

A more homogenous structure

Even though the new molecular quantum nanosensor (MoQN) works in the same way as these conventional devices, it does not suffer from this problem, explain Nobuhiro Yanai of the University of Tokyo and Hitoshi Ishiwata of the National Institutes for Quantum Science and Technology (QST), who led this research effort. This is because it has a more homogenous structure and does not contain any defects. Instead, it is made by embedding molecular spin qubits, in this case fabricated from pentacene, in nanocrystals of para-terphenyl. This design makes the structure uniform on a molecular scale and preserves the quantum coherence of the spin qubits. It is then coated with Pluronic F127, which is a biocompatible surfactant.

By detecting the spin direction of the “excited triplet state” of the pentacene qubits using a technique known as optically detected magnetic resonance (OMDR), the researchers can precisely determine the temperature of the qubits’ surroundings from the OMDR peak position. When they tested their method inside the cytoplasm of cancer cells in vivo, they found that the intracellular temperature was consistently higher than the surrounding medium.

Yanai says he embarked on this study after reading about the work of Sam Bayliss’ group at the UK’s University of Glasgow, and Ashok Ajoy’s group at the University of California, Berkeley in the US on OMDR in pentacene-doped para-terphenyl crystals. He says he immediately got the idea that nanocrystals of this material could be used for quantum sensing inside cells. This was because his group had already developed such nanocrystals for a different purpose in previous research.

Ensuring biocompatibility

“I then spoke with Hitoshi Ishiwata, who is an expert in quantum sensing using NV centres,” he recalls. “While many molecular qubits have been developed to date, there had been no examples demonstrating their sensing ability within living cells.”

The project required materials science expertise, he tells Physics World, and in particular, finding out how to reduce the material to the nanoscale and ensuring it was biocompatible.

“We already knew that nanodiamonds are good quantum sensors for temperature measurements, but I had noticed a practical limitation: their ODMR spectra often vary significantly from particle to particle,” he says. “This spectral dispersion can introduce errors, especially when trying to perform precise measurements at the single-particle level.”

Replacing hydrogen with deuterium

The researchers thought they had overcome this problem during the first run of their experiments because they found that different particles showed identical OMDR spectra. However, their joy quickly waned when they observed that the spectra were still broadened by hyperfine interactions between the pentacene-doped para-terphenyl molecules’ electron spins and hydrogen nuclear spins.

To improve the spectral resolution, Ishiwata says he suggested chemically modifying the molecule by replacing the hydrogen in it with deuterium. And the technique worked: “the hyperfine broadening was strongly suppressed, allowing us to determine the OMDR spectra much more precisely.”

These findings, which are detailed in Science Advances, show that MoQNs are a chemically versatile platform for quantum sensing in living cells and that they can operate directly inside them while maintaining the precision needed for absolute thermometry, he says. Their appeal also lies in in the fact that their structures can be easily modified.

It will not all be plain sailing, however, adds Yanai. MoQNs cannot yet target specific organelles within cells, so endowing them with this targeting capability is an important future challenge. “What is more, their size has been limited to around 200 nm so far, so creating smaller MoQN particles will be crucial,” he says.

The post Molecular spin sensor takes the temperature of cancer cells appeared first on Physics World.