Lune

S&P2024Top-tier venue

Nebula: A Privacy-First Platform for Data Backhaul

Jean-Luc Watson, Tess Despres, Alvin Tan, Shishir G. Patil, Prabal Dutta, Raluca Ada Popa

2024Year
5Citations
2Top-tier citations

Abstract

Imagine being able to deploy a small, battery- powered device nearly anywhere on earth that humans frequent and having it be able to send data to the cloud without needing to provision a network—without buying a physical gateway, setting up WiFi credentials, or acquiring a cellular SIM. Such a capability would address one of the greatest bottlenecks to deploying the long-tail of small, embedded, and power-constrained IoT devices in nearly any setting. Unfortunately, decoupling the device deployment from the network configuration needed to transmit, or backhaul, sensor data to the cloud remains a tricky challenge, but the success of Tile and AirTag offers hope. They have shown that mobile phones can crowd-source worldwide local network coverage to find lost items, yet expanding these systems to enable general-purpose backhaul raises privacy concerns for network participants. In this work, we present Nebula, a privacy-focused architecture for global, intermittent, and low-rate data backhaul to enable nearly any thing to eventually connect to the cloud while (i) preserving the privacy of the mobile network participants from the platform provider by decentralizing data flow through the system, (ii) incentivizing participation through micropayments, and (iii) preventing system abuse.

Ask about this paper

Your agent reads all of it.

Lune indexed this paper to the last equation, along with the top-tier papers that cite it. Ask a question and the answer quotes them.

Questions to start from

Your agent calls

Luneget_paper_fulltext

Ask in Lune

Free to start. No credit card required.

lune papers fulltext 90a31e3a-6f93-4953-bce9-451d1da9fd10

Cited by top-tier papers2

Ask how each one uses it

Builds on5

Related papers

Dusk over the sea between two cliffs drawn in fine vertical lines