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by matthewfcarlson 4 hours ago
Is the threat model tracking across multiple apps to correlate what you're doing? In that case, a single app wouldn't show you the fudging.
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```Based on a binomial/Poisson distribution and a baseline of 21 million U.S. device sales per release, a fingerprint relying on "seconds since setup" fails to uniquely identify individuals. In the high-density Early Adopter phase, you will share your exact setup second with an average of 1.01 other people (a total matching pool of ~2 people). Six months into the cycle, you will still share that second with an average of 0.68 other people.```

In the U.S., device setup time (to the second) very conservatively gets you clubbed into a single group of 100 individuals as an "advanced persistent threat" tracker. Even compressing activations to "80/20 during business hours" the math kindof maxes out at a pool of ~5 people, and assuming worst case "20x" of that still means you're still pretty darned identifiable.

If you get ~6-8 more bits of entropy (eg: Device Type + Capacity is easily 2-3 bits, and Time Zone is probably another 2-3 bits) you're cooked!

Just using IP address, device storage, device name, and similar signals, we can identify a user. It isn’t difficult to correlate these data points. Apps like Facebook also force developers to use their SDKs for even small features.