# MPCStats | Devcon SEA

- Channel: [Devcon](https://streameth.org/devcon)
- Date: 2025-10-09
- Duration: 08:29
- Topics: Science & Technology
- Watch: https://streameth.org/watch/yt-wCp7Zsjou7w
- YouTube: https://www.youtube.com/watch?v=wCp7Zsjou7w

## Description

MPCStats is a framework allowing data consumers to query statistical computation from either one or multiple data providers while preserving privacy to those raw data. We support standard statistical operations, including nested and filter ones. Data providers do not leak their data and data consumers can be convinced the computation is done correctly.

Speaker(s): Kevin Chia, Teeramet (Jern) Kunpittaya
Skill level: Intermediate
Track: Applied Cryptography
Keywords: Tooling, Privacy, MPC, Public good, verification, computation

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Devcon SEA was held in Bangkok, Thailand on Nov 12 - Nov 15, 2024.
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## Transcript

[Music] [Music] yeah hello everyone so um we're NPC stat team at PSC so today we'll introduce our project and it's currently work on by Jour by Jour and I and kazum yeah so the goal of our project is to build a framework that allows users to carry statistical computation across different data providers well guarantee the data Prov privacy and also the correctness of the result we've implemented um common statistical operations using MP speeds which is a well well-known MPC framework we've supported 12 statistic statistical operations and also some common table join and array conc concatenation and filtering so um users can Define computation like this and we also integrated TS notary so that the inputs to NPC are authenticated from some well-known websites so that we can prevent garbag in garbage out situation all right thank you Kevin so basically right now we are talking about NPC right so intuitive approach for NPC is that having all parties data providers data consumers to join as a computation parties right the bad things the I mean the good thing for us let say is that it's fre verifiability because everyone is in the same like competition set right so they know like what computation is done right I request mean I know that this guy just compute mean for me right the bad thing is that the data providers consumers everyone need to be online at the same time and it's really hard right for many numbers of data providers especially when the number of data providers grows the computations grow Skyrocket so badly so how to solve that right we use another approach called client interface which basically means that the data providers and data consumers are not in the computation parties so there's three phase the first phase is that data provider secret share the data through some delivery BRS they can log in share data and log out and then another set of computation parties compute data and once it's ready data consumer just loog in to get it out so this is good because they now the data provider and consumer doesn't need to be online at the same time which makes sense and it also doesn't grow with the number of data provider because the cost of the MPC computation is actually from the number of the parties in the computation parties the bad thing is that the data providers and consumer now need to trust the Pary is right it depends on set up is say malayas we need to trust at least one of the party is right and again because we are not joining in the MPC competition party itself we have no idea like what is the function that they calculate is actually the one we want but again the trust is the same that if you trust that at least one for the Malaysia sitting right of the computation parties honest we can be sure that they just run the computation that we want like mean or median or anything we want so use case we are thinking about cross departments data sharing government verifiable salary data any survey research for policy planning and yeah many more let us know so demo time so this is C up and running we still under maintenance the final optimization because it's pretty big so we will notify soon but it's pretty interesting to explore e balance in equality at Defcon so what it means like you guys can use your binance to share it privately we won't know your binance balance but then we will be able to calculate the interesting stat we will show later but you guys should join this group first so we will notify by today tomorrow once the docker file is smaller so that it can make sense to run in this like internet in defon so the cat right because we want to be up front so we will only allow you to share share like privately the free E in your spot balance of binance and again the parties who still learn the number of digits although this is comes from the the limitation of the is not itself that the Pary still know like the number of digits of your binance balance but again we won't know actually the number and again this is the trust assumption that we trust that our three party doesn't collude right and yeah please please join this telegram group we will get up soon and anyone who join will get a chance to win an nft and a win a lottery as a actual cash so yeah so this is just to Quick go through it will already be in our R me in our demo so get binance API key just go yeah binance API key everyone know how to do that get the API key and secret key make sure it's read only and then yes so notor this this is only our script that you need to run you just get clone and you run and make sure that your Docker is opening and running on your laptop and then yeah you just run this again this is just one line and e address is just address for receiving the price this is not not the address for the binance this is just for to send the price if you want one and yeah this is the website so we are having Max E balance of Decon mean median number and Genie coefficient to make sure of the inequality so yeah join us thank you so much thank you Kevin John any questions oh that's too far okay you got it uh hey uh great talk um it's not clear to me are you guys trying to collect like aggregate statistics from like multiple parties and if that's the case and that's the US case um did you explore something like a PR like M like system you know using like function secret sharing uh I don't think MP speed support that so I'm kind of curious it should be much much much more efficient yeah thank you so much for suggestion yeah I think we looked at through some of it but this limitation mostly is through the number of data providers so right now again like FG multi key functional encryption secret trying uh yeah we look through some of them and we're thinking of using some but again the limitation right now is that the state-ofthe-art MPC of a huge number of data provider is still matters and we think again because we make sure right that we don't want the competition to just grow indefinitely with the number of data provider so we still choose this but thank you so much for for yeah yeah yeah so just look at function secret sharing I think it would really really boost your result thank you I appreciate function secret sharing note do we have any other questions oh there's one hi I was trying to scan the the TG um QR code that you showed just now and it says link expired for me uh is it just t. me/ MPC stats that's a link uh yes yes okay sorry about this so t. me/ MPC stats yeah any other question can I ask a question um I know that the the Federated rate um Federated learning is similar to you know preserving privacy and then the medical hospitals they're having a lot of um you know confidential data of the patients so they use Federated learning I just wonder what you're presenting how different it is from Federated learning sure yeah so basically Federated learning is like you trains offline right like data do there and then you send the update on the gradient descent or anything to your machine learning up in the air right so basically you train everything update but now MPC it means that you train do gather data from different parties and compute at the same time so for Federate ring so it can use actually it depends on what types of thing you use but it can also use MPC itself so but yeah when it comes to rning people still consider like not too many parties or advance but when we thinking about stats we thinking about like population so we wish to make it more scalable in ter like number of data providers itself but yes I think a lot of Federate learning techniques to use MPC but we just want to make sure that MPC framework that really scalable to a huge number of data providers yes okay thank you