Categories: FAANG

Local Pan-Privacy for Federated Analytics

Pan-privacy was proposed by Dwork et al. (2010) as an approach to designing a private analytics system that retains its privacy properties in the face of intrusions that expose the system’s internal state. Motivated by federated telemetry applications, we study local pan-privacy, where privacy should be retained under repeated unannounced intrusions on the local state. We consider the problem of monitoring the count of an event in a federated system, where event occurrences on a local device should be hidden even from an intruder on that device. We show that under reasonable constraints, the…
AI Generated Robotic Content

Recent Posts

Omnigen 2 is out

It's actually been out for a few days but since I haven't found any discussion…

18 hours ago

From fear to fluency: Why empathy is the missing ingredient in AI rollouts

Empathy and trust are not optional. They are essential for scaling change and encouraging innovation,…

19 hours ago

What Satellite Images Reveal About the US Bombing of Iran’s Nuclear Sites

The US concentrated its attack on Fordow, an enrichment plant built hundreds of feet underground.…

19 hours ago

Half of today’s jobs could vanish—Here’s how smart countries are future-proofing workers

AI is revolutionizing the job landscape, prompting nations worldwide to prepare their workforces for dramatic…

19 hours ago

Spline Path Control v2 – Control the motion of anything without extra prompting! Free and Open Source

Here's v2 of a project I started a few days ago. This will probably be…

2 days ago

STARFlow: Scaling Latent Normalizing Flows for High-resolution Image Synthesis

We present STARFlow, a scalable generative model based on normalizing flows that achieves strong performance…

2 days ago