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Merge pull request #229 from mhchia/docs/add-mpc-stats
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docs: add MPCStats
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kalidiagne authored Nov 5, 2024
2 parents 56c047f + 4249b20 commit cd9cfb0
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2 changes: 2 additions & 0 deletions data/projects.ts
Original file line number Diff line number Diff line change
Expand Up @@ -18,6 +18,7 @@ import { maci } from "./projects/maci"
import { maciPlatform } from "./projects/maci-platform"
import { mopro } from "./projects/mopro"
import { mpc } from "./projects/mpc"
import { mpcStats } from "./projects/mpc-stats"
import { nfctap } from "./projects/nfctap"
import { OpenPassport } from "./projects/openpassport"
import { p0tion } from "./projects/p0tion"
Expand Down Expand Up @@ -52,6 +53,7 @@ export const projects: ProjectInterface[] = [
rln,
zkitter,
mopro,
mpcStats,
maci,
wax,
discreetly,
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35 changes: 35 additions & 0 deletions data/projects/mpc-stats.ts
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@@ -0,0 +1,35 @@
import { ProjectInterface, ProjectStatus } from "@/lib/types"

export const mpcStats: ProjectInterface = {
id: "mpc-stats",
image: "mpc-stats.png",
name: "MPCStats",
section: "pse",
projectStatus: ProjectStatus.ACTIVE,
content: {
en: {
tldr: "A framework for private and verifiable statistical analysis across multiple data providers.",
description: `
## Overview
MPCStats is a framework that enables data consumers to query statistical computations across multiple data providers while ensuring privacy and result correctness. By integrating privacy-preserving technologies such as ZKP, MPC, and FHE, our goal is to provide tools and guidance for integrating privacy-preserving analysis into their workflows. We also aim to identify real-world applications that can benefit from this framework.
## Features
- **Privacy-preserving and verifiable statistical analysis**: Allows data providers to keep their inputs confidential while giving data consumers the assurance that computations are performed accurately and securely.
- **Data validity**: Integrates TLSNotary to authenticate inputs from verified web sources, ensuring data consumers can trust that data inputs are genuine and accurate.
## Use Cases
- **Cross-department data sharing and surveys**: Enables secure, private data sharing across government departments for streamlined operations and collaborative analysis.
- **Healthcare research**: Aggregates data from sources such as fitness apps and sleep trackers, allowing researchers to uncover relationships between health factors, such as fitness and sleep patterns.
- **Salary survey**: A verifiable and anonymous alternative to platforms like Glassdoor, where users can contribute salary data with privacy guarantees.
`,
},
},
links: {
github: "https://github.com/ZKStats",
website: "https://t.me/mpcstats",
},
tags: {
keywords: ["MPC", "statistics", "data analysis"],
themes: ["build"],
types: ["Legos/dev tools", "Lego sets/toolkits"],
builtWith: ["MP-SPDZ", "tlsn", "python"],
},
}
Binary file added public/project-banners/mpc-stats.png
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