As apps quietly trace your steps and advertisers stitch together your life from coordinates, a new cryptographic breakthrough marks a sharp turn toward digital self-defense. Researchers in Germany have devised a method to confirm a person’s physical presence at a location, without revealing that location at all.
The project, led by a team at the Technical University of Munich (TUM), rethinks how digital systems can validate truth without trading away privacy. Their technique, recently shared at a leading cybersecurity conference, taps into an elegant mathematical concept known as zero-knowledge proofs—a system that lets one side prove something to another without disclosing the information behind it.
TUM’s solution doesn’t try to hide location after the fact. Instead, it rewires how location sharing works entirely. It lets users prove they were within a certain geographic area, but masks the exact spot. Whether it’s a city district or a public park, the recipient of the proof only learns that the user was somewhere within those bounds—not which street, not which bench.
But the real innovation lies under the hood. Most systems in this space rely on simple integer calculations. TUM’s version steps into the world of floating-point numbers—the kind used by actual processors in modern devices. This change might sound trivial, but it resolves a pile of subtle errors that have plagued previous systems, especially when more complex calculations come into play.
In practice? The system runs fast—nearly instant. A person can generate a proof of proximity in less than a third of a second. No major battery drain. No lag. And no risk of oversharing.
Digital health, autonomous mobility, privacy-preserving AI—these are fields hungry for tools that can validate without exposing. TUM’s approach may offer a versatile foundation.
For once, “location sharing” doesn’t have to mean oversharing.
Image: DIW-Aigen
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The project, led by a team at the Technical University of Munich (TUM), rethinks how digital systems can validate truth without trading away privacy. Their technique, recently shared at a leading cybersecurity conference, taps into an elegant mathematical concept known as zero-knowledge proofs—a system that lets one side prove something to another without disclosing the information behind it.
Reclaiming Control Over Location Data
Location data sits at the intersection of convenience and vulnerability. Phones log it passively. Apps request it routinely. Most users, meanwhile, hand it over without much thought. But movements can reveal more than routes—they can uncover habits, jobs, even affiliations. In one now-infamous investigation, commercial location data traced a government official's phone to multiple high-security sites.TUM’s solution doesn’t try to hide location after the fact. Instead, it rewires how location sharing works entirely. It lets users prove they were within a certain geographic area, but masks the exact spot. Whether it’s a city district or a public park, the recipient of the proof only learns that the user was somewhere within those bounds—not which street, not which bench.
How It Works (Without the Math Headache)
At the core of the system is a clever grid—hexagons, stacked and layered, covering the globe. Each cell represents a chunk of space. Depending on the application, a user can prove presence in a broad area or dial in to something smaller, like a single block. Still, the coordinates themselves remain undisclosed.But the real innovation lies under the hood. Most systems in this space rely on simple integer calculations. TUM’s version steps into the world of floating-point numbers—the kind used by actual processors in modern devices. This change might sound trivial, but it resolves a pile of subtle errors that have plagued previous systems, especially when more complex calculations come into play.
In practice? The system runs fast—nearly instant. A person can generate a proof of proximity in less than a third of a second. No major battery drain. No lag. And no risk of oversharing.
More Than Just “Near Me”
The most obvious use case is proximity checking: two people verifying they’re in the same general area without swapping GPS pins. But the implications stretch further. The building blocks of this method—especially the floating-point zero-knowledge circuits—aren’t just locked to geography. They could eventually help prove that a measurement was taken correctly, or that a device behaved as expected, all without disclosing raw data.Digital health, autonomous mobility, privacy-preserving AI—these are fields hungry for tools that can validate without exposing. TUM’s approach may offer a versatile foundation.
A New Layer of Trust in a Distrustful Ecosystem
The digital world is built on proof, but not always on permission. What this research does is put the user back in control of what gets revealed, and when. It’s not just about hiding data—it’s about reshaping how systems ask for trust.For once, “location sharing” doesn’t have to mean oversharing.
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