Zero Knowledge: Solution for Digital Identity? w/ Leo Fan

I spoke to Leo Fan, co-founder of Cysic, about what zero-knowledge proofs actually are, and why they might be one of the more promising answers to the internet's identity problem.

We dig into how a ZK proof lets you prove something is true without handing over any identifying personal information, why that matters as digital identity systems become pushed by governments, and Cysic's model for verifiable compute. Leo also breaks down why the hardware and cost problems around ZK have kept it from mainstream identity use so far, and how Cysic's network lets you use your own hardware to help generate these proofs, rather than leaving that compute in the hands of a few large players.

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Transcript

SPEAKER_01 0:00

But uh at the time of the deployment, we find like the the proof generation is like too small. Even we use a very large AWS uh instance, it's still like very slow, which like inspired me to design some special hardware for that. For instance, like I want to say like transfer probably like 10 10 bucks online, but I need to prove to the channel or like to some like uh authority that my bank balance is like more than $10. So like I can prove that part, but without releasing the exact uh balance number in my bank account.

SPEAKER_00 0:36

What are the implications of this technology? Is the ability to selectively disclose specific bits of information about yourself over a digital space, which is you know historically really hard to do because you you produce so much data when you're uh over the internet.

SPEAKER_01 0:50

Seems like in vacancy, you don't need to trust anyone. Like you just uh trust the math, and the math like you can do it by yourself. And we are not creating like a honey pod like for uh for the hackers to hack.

SPEAKER_00 1:03

Hi everyone, you're listening to the Blockchain Socials podcast. I'm Josh, and I am here today actually in potentially my new studio that I'm going to be using uh going on into the future. So more news on that that I will share uh soon. But before I go into that, um I wanted to introduce my guest for today. His name is Leo Fan, and he is the uh founder of Cysic, which is a super interesting project um building called an on-chain compute network. But before I butcher trying to explain it, um maybe Leo, if you want to give a quick introduction to who you are and what CySic is.

SPEAKER_01 1:43

Yeah, sure. Um my name is Leo Fan. Like I uh I got my PhD from Cornell in cryptography. After Cornell, like I did some uh research engineering job at NIST and Agrand, then started as an assistant professor at Rutgers. Um yeah, so when I was at Argoland, like uh we we delivered the first uh decade bridge became Agrand AC and Agorland Semana, but uh at the time of the deployment, we found like the the proof generation is like too snow. Um even we use a very large AWS uh instance, it's still like very slow. So which like inspired me to do something to like uh design some specialized hardware for that. Um yeah, so the the word like CISIC is a combination of two words. The first is like cipher, uh and the second part, the SIC is like coming from like uh ASIC. So it's a combination of like building some specialized uh hardware for cryptography. So that's like how we like started Cysic. Um and like while doing Cystic, like we we do a lot of things, like we do like the GPU and FPG acceleration, and we also did some like work on ASIC design for um for the K.

SPEAKER_00 3:00

So maybe just to help listeners, just in case they don't know what some of these terms mean, ASIC is an application-specific integrated circuit, if I'm not mistaken. It's kind of like specialized hardware. Often you hear about it in the context of mining Bitcoin. You uh you you get ASICs uh hardware in order to uh mine Bitcoin really, really well because it's a specialized hardware that's really good at specifically the thing for um mining Bitcoin, for example. Um and then uh if I'm not mistaken, cipher is also a cryptography term. Yes. Um that I believe is like, I if I'm not mistaken, is it it's the key? Is the cipher the key in like a cryptographic secret kind of way to explain it?

SPEAKER_01 3:41

So like in the encryption part, like the encryption world turned in this like painted into ciphertext. So ciphertext is uh encrypt kids uh plaintext.

SPEAKER_00 3:51

So ciphertext is kind of like the secret itself, I guess. Yeah. Um so jumping off a couple of levels from you know uh assuming you guys understand a little bit about cryptography, which is just the math around uh sharing secrets and uh saving data and memory for computers, um zero knowledge cryptography or ZK cryptography is a different type of cryptography that's a little bit more advanced and is kind of on the on the bleeding edge of things. Um maybe you can explain a bit what is zero knowledge cryptography and why is it you know, why is it expensive to generate and and use right now?

SPEAKER_01 4:30

So we can like treat the ciphertext we just talk about as encryption or like some representation of the plaintext, but in the in the ciphertext way. Uh so like for ZK, you can think about like we so they k to computation is what ciphertext is to uh plaintext. So like we basically compress a lot of like a computation into a like very tiny uh B string. And this B string will represent this like computation, but this like B string is not like the harsh stream, they still have some like structure inside which will enable people to trust you if they verify that the the B string you handle to them uh satisfies some requirement. So that's like how you can see uh the the K the knowledge part. So it's like uh a representation of the of the computation you just uh carry out. Yeah. And and why it is like useful, it has like two nice properties. The first one is uh their knowledge less, and the second second one is the succinctness. So their knowledge less means like it will preserve the like the privacy uh and without releasing the privacy, the private part like to you. Like for instance, like I want to say like transfer probably like 10 10 bucks online, um, but I need to prove to the say to uh to the channel, like to some like uh authority that my bank balance is like more than $10. So like I can prove that part, but without releasing like how uh like what's the exact uh balance number like in my eye in my bank account. So like I handle you this like uh this like zK proof, and then you can verify and then trust that my bank balance is like is larger than like 10 bucks, and then you can do the transfer. So that's so uh the knowledge part. The second part is succinct. So the succinctness means like the proof is like very short, it's probably like several hundred bytes or several hundred kilobytes, so it's a very small uh proof, which um which like you can use a proof to encode and like a very large net computation. So that's the first part of the succinctness. The second part is although the proof generation is like takes a lot of time, but the proof verification is like super, super fast. You can verify the key proof on your cell phone like in less than 15 milliseconds, and with a very very little uh computing resource, then you can do the verification. So next as I say we have this like MySIC app, which you can download it and then to verify the proof we generated like in part of our network on your cell phone. Yeah. So that's like two nice properties that their knowledge has and succinctness of like the key.

SPEAKER_00 7:30

Right. Yeah. I think one of the ways that I've also heard people try to explain Zero Knowledge Proofs is the example of like in the United States, for example, where if you want to go inside a bar, you have to show your ID, uh, your driver's license. And you know, you give your driver's license to the bouncer, and he doesn't he not only sees that maybe you are or are not old enough to enter your above 21, they know exactly your birthday, they know your full name, they see your address, they see a lot more information than maybe they necessarily need to know. So this kind of it's it allows you to say to the bouncer, I'm over 21 without giving any other information, without getting any any leakage of unnecessary information. So it's kind of like a way of doing selective disclosure, I guess is this this is the the zero knowledge part at least aspect of zero knowledge proofs. And I think that's why it's interesting from uh you know, what are the implications of this technology is the ability to selectively disclose specific bits of information about yourself over a digital space, which is you know historically really hard to do because you you produce so much data when you're uh over the internet and everybody, you know, if you if you own the platforms or if you own a lot of the the piping between everything, then you know uh maybe a bit more or you've given out more information than you intended to give out. Right. Yeah. Um and then succinctness, it's also good for compressing data. I guess. Yes, yes, yeah. It's kind of how I think about it. Yeah. Um are there any like um maybe specific real-world examples of zero-knowledge proofs and cryptography kind of um in use that like you know the average person may be able to relate to for you?

SPEAKER_01 9:10

Right, yeah. So like if so, like we all know like the uh I uh like both uh Bitcoin and Ethereum, they're like public ledger where like all people can check like the the balance or like how how many coins they have like in one uh wallet address. But there are some like some privacy-oriented uh blockchains such as like Zcash or Alio. They like if you do the they can basically shield the number of like tokens like you have in your wallet so that people cannot check the exact number on all the transfer, probably I would say like 80% of the transfer also like happen privately and which preserves some privacy of like uh the traders or like some other guy like who use the uh the blockchain. So that's like on the the knowledge nice part. And the second part is on the uh succinctness. We can use the succinctness like to scale up another blockchain. So like for take Ethereum, Ethereum for uh for instance, like if like how Ethereum like uh validates the transactions that they re-execute all these like transactions in Ethereum. So that's like which is like why they put a guess limit for for the like for a block. But in instead of like re-execution, you can generate a zK proof. Where like since like a zeker proof is like one proof, you will generate and everyone can verify it, and then if it pass the verification, then uh then they will like trust like the the statement in this proof is true. So instead of like re-execution, you can just verify some zK proof, which proves uh that all the transactions uh they are like valid. And the verification of like the zek proof takes a very, very small uh guess. So which which means it will increase the guess limits, which you can like have like more transactions in in one block like for Easily. So that's like two uh nice applications of uh they can in blockchain.

SPEAKER_00 11:22

Right. Privacy and scaling. I think kind of I think what's what's important to understand for a lot of for some users, at least when I've tried to explain cryptography with them is that like a lot of cryptography can be used for both privacy and scaling, and that they're kind of like um the same property. Yeah, like the same property of a th of of of this math that you're that you're using in these systems can be used for like things that you don't think are related, but uh they end up being related in in these types of systems, which I think is really, really interesting. It's kind of like a when I realized that I was like, oh, this is why it's like you know, quite expansive what what you can think about doing with this.

SPEAKER_01 12:01

Yeah, yeah.

SPEAKER_00 12:02

So you mentioned that like proof ZK proof generation is um fairly expensive or it's clo costly, it's kind of slow. Um it's still you know a type of technology that people are figuring out how to do um better, faster, et cetera. Um but I'm curious why, you know, where where does that like cost come from? Uh why is ZK proof generation so much slower than like say you know other forms of of cryptography that we're already using today?

SPEAKER_01 12:31

Yeah, so like I I guess uh other crypto tools like we are you using today is like uh encryption, digital signing, and also probably like some hash functions. So like compare against the these tools, the uh the data handled by uh by the cable is like we much longer. So like a typical ZK statement will handle this like degree of like very large uh uh degree polynomials. And the the degree is unit, like two to the 24 or something. So it's a very large uh polynomial. And for and the coefficient for this polynomial is also uh 256-bit none. So it's a large polynomial with a lot of like uh data in there. And handle this kind of polynomial will require enormous uh computing resources to do that. And also the computing resources, like when they do the uh process, they also need to communicate with each other, which means like you also need to have very high bandwidth to support uh the transmission of the data between this like processing unit. So that's the like two most important parts in the competition, like very large uh computing resource and then and a very high uh bandwidth to support the processing. So which also explains like why it's quite expensive to generate a data proof. You need to have a machine that's like powerful enough to do both things like very efficiently.

SPEAKER_00 14:04

Right. So it's just uh basically it's more mash, yeah, is uh is the simple answer. Yeah. Bigger numbers, yeah, bigger numbers.

SPEAKER_01 14:12

Yeah, bigger numbers uh takes longer time to both like computes and also to to transfer the thing.

SPEAKER_00 14:19

Right. So I guess uh so this is kind of like my understanding, at least, is that then um you know, like your average computer hardware is not necessarily built at the moment to be generating zero knowledge um proofs. Yes. Um and so I guess this is kind of why, if I understand correctly from what you guys are doing, uh that you guys also provide hardware, like a a network of hardware for people to use to generate these proofs. Um yeah, do you want do you want to talk a little bit more about the hardware side of things?

SPEAKER_01 14:52

Yeah, sure. CySink is a compute-file network. So by compute file, we mean like we turn this like computer resources into some early machines for you. You can plug in your like servers, your laptop, or even your cell phone into our network to do something something like in the computation. And of course, like we categorize like uh each we categorize this hardware into the different groups, which is like responsible to do different things. Like for instance, if you plug in your like server, public is powerful enough to generate some DK proof in a short period of time. And we also use this like uh servers to do some like AI inference for us. So that's like the server side. If you plug in your like laptop or even your cell phone, which is like not powerful enough to do the the two things I just mentioned, like then we assign this like um they key verification, AI verification job to you, which like you're not very powerful uh computing how uh hardware still can handle that, and also some other things like uh yield. And all the things were wrong in the in the back end, so you won't be able to notice any difference like in using your hardware.

SPEAKER_00 16:06

Yeah. Right. Yeah. So there's uh there's generation, the proof generation, which is taking in all the inputs that make up your your zero knowledge proof, and you know, depending on how you how you're uh um like setting it up, you create you generate a proof which is like kind of a reference to you know all these inputs and gives you a kind of answer, but then that answer has to be verified by some by you know the person that receives the answer to double check to know that this proof is saying what you it's claiming to say. And if I understand correctly, the generation is much more uh compute intensive than verification.

SPEAKER_01 16:48

Yes, yes, that's right.

SPEAKER_00 16:49

So there's these these these two types of compute, uh verification. You know, if you got uh probably any any probably laptop or or phone can do verification. Uh the generation maybe you can do, but it will take a lot longer than like you know, a beefier machine. Um but you guys are basically, if I understand correctly now then, you guys are creating a kind of network where anybody can can bring whatever hardware they got and they could potentially make a little bit of money off of it because other people are paying for the verification and the generation of ZK proofs uh on the network. Nice, that's super cool. It reminds me of I don't know if you remember one of these early, I think I think that was uh Golem maybe was like one of the first kind of attempts to do something like this, if I'm not mistaken. I think there are other ones. It reminds me of like these proof of useful work blockchains that you used to have back in like 20 uh 2017. Yeah, maybe yes.

SPEAKER_01 17:43

Yeah, so so that's like yeah, so at that time, like people were saying like uh all this like Bitcoin mining is like a waste of uh computer resources. It's like you produce uh some like specialized hardware which will also cost a lot of like electricity in computing the hash. So people think like he probably instead of doing that, like we can use use uh like the resources, whether it's like in electricity or computing power to do some like real jobs for human beings. Yeah, so that's uh time like in 2014 till 2017, I think. Yeah, so since this since like my like before uh coming to Cornell for PhD, and like I did some like Bitcoin mining uh back then, yeah, for for uh for several years. So like and the idea of like using some specialized hardware to accelerate the case, also as you mentioned, like this idea was also inspired by Bitcoin mining.

SPEAKER_00 18:44

Okay, nice. Um is uh actually um which uh network does Sysek uh connect to? Which blockchain networks?

SPEAKER_01 18:53

Uh yeah, so right now we are like proving um so it also depends on the market. So so problem like last year, like SySek is a biggest prover for for like several uh large like nail tools, including uh scores, equinq, yeah, things like the these nail tools, they their job is to scale up Ethereum. So they generate a lot of like transactions and they need awesome, which means they need a lot of like computing resources like to generate the key proof for them. And like so, for instance, like we successfully like reduce the proof generation time from like 1.5 hours to about like 20 20 minutes on a two-car uh 249k uh GPU card like machine. Yeah, so so that's why like we so this like layer tools, they they want to work with us to reduce the burden of like generating vaccine proofs. But like uh so that's like something uh that's a situation for us uh for next year. But as you can see, like all these layer tools, they are not doing very well right now. Yeah. So so like we shift like uh some of our computing resources to support uh Ethereum and also to support some perp uh perp decks. Um yeah, this perp decks, they also need to generate a ZK proof for each uh for each transaction on their decks. So like so that's also like a very large number to not large number of like ZK proof to generate.

SPEAKER_00 20:29

Okay, are these perp do they verify those ZK proofs on chain or are they just generating a proof?

SPEAKER_01 20:36

Um so like like our process is like we we like thin, we we can talk about the lifespan of like a ZK proof in inside network. So so like for for each like task we receive from say like this like perp decks, we pick like several like random uh proofers uh to generate the proof. And then like we pick a large number of like verifiers, which like on your cell phone or on your laptop to verify the proof. After a proof is like verified, say by uh eight out of like 10 verifiers, we call it this proof is like settled, then we then we put it on uh sizing network and uh and also additionally we send the verifier proof to to the perp decks. So the proof is already like settled in our chain, and some of the problem, like I I guess uh the the perp decks or like they don't have the energy to verify like each proof, they just do some like sampling on the proof uh already settled by us, like to do to check the uh validity of the proof. Yeah.

SPEAKER_00 21:46

I see. Interesting. So you have like uh the network also has a level of kind of redundancy, I guess, where you you want to you want to be able to have trust in the in the proof, and so you have. A few at least people run the same proof or verify the same proof uh to make sure that it's valid. Yes.

SPEAKER_01 22:08

Yes, I'm sorry.

SPEAKER_00 22:09

Yeah. So maybe we could talk a little bit more about compute fi. Uh I think it's interesting. I think there's there is like this uh uh general I mean I've just I I've I've never really in engaged with any of this, but I've seen some stuff of like um you know people trying to financialize a bit of their their like the computes on their on their computers to sell that as like future compute used in AI inference or something like that. Um I I'm wondering if you can explain a bit like how how do you see ComputeFi, what is it, and like um what does this future hold for us?

SPEAKER_01 22:53

Yeah, so uh as you can see, probably like there are like several authors similar platforms such as like iodanets or some some some others. So but but the like the iota nets or like some other, they are just creating a platform where like people plug in their uh servers there and and uh wait to be like rented or like used by others. So it's basically like AWS or like vast uhai, this kind of platform, but they are in in the blockchain or crypto worlds. So like SciSec differs uh from these uh competitors in a very significant way. So like in addition to creating uh creating this kind of like platform, we also bring some like real jobs uh to be computed uh by the by the servers in size network. Say, like for instance, the the key pool generation is like one thing, and also we have this like uh a lot of like AI products on SISE network, which also consume the under uh consume the tokens uh it's like generated by the underlying machines. So like in addition to just uh uh creating a platform, we are we are bringing some like real jobs for the for the servers on SISE network to process. So that's a very big, big difference. Yeah.

SPEAKER_00 24:23

Do you think like in the future, you know, one one potential well, I guess the thing that kind of you're describing, just to step back a bit, is almost like a you know, this this uh it's almost like a meme to me, but like this meme of the decentralized cloud, so to say, of like computes or computers being able to connect from anywhere to take part in this network and to provide that infrastructure in a way that is resilient uh and redundanced, at least at par with you know other types of cloud providers. Um and that people would be able to kind of like you know uh have almost like have have like make money off of the data center you have at home. Yes, yeah, yeah. You know, rather than necessarily the mass build-out of giant data centers that's maybe going on right now. Maybe one alternative is we could use the excess computes that we already have available to us with everyone's consumer hardware rather than needing to overbuild you know all these amounts of data centers, this could be one kind of alternative uh to that.

SPEAKER_01 25:36

Yeah. Yes, that's right. Yeah.

SPEAKER_00 25:39

So yeah, are there any other uh I guess the um yeah, are there any other non blockchain related ZK um examples that you're you're particularly interested in?

SPEAKER_01 25:54

Um Right, yeah. So like as you you can uh as you mentioned before, like the ID thing is like one uh very good example. Like in addition to showing up in like your ID, you can just uh generate a digit push. Uh saying like you are like uh older than 21, then you can enter the uh enter the uh the bar. And another example is like there are some um events like um say like probably like last year or the year before before last year, there is a there is a death count in in Thailand. And when like if you are like a local like in in Thailand, then you can apply for some uh apply for a special discount on the ticket for for the event. And how how you like proof you are like a local like is like previously like you just upload your your passport and then you are showing that you are local. But like that will reveal a lot of information you don't want to reveal. Uh so like very nice way of like using ZK to wrap around it, like you download a software and then you generate the ZK proof uh of your passport showing that you are uh from like Highland, and then you upload only the ZK proof to uh to the TK website, and then then after they verify it, then you can go the like special discount. Yeah, so that's yeah, it's basically digital ID, and you can use a digital ID like to do a lot of like things, yeah.

SPEAKER_00 27:32

Right. I and this is like I mean, this is super interesting to think about just in the current context with the amount of legislation that's being passed right now, um, requiring people to prove that they're you know over 18 or whatever to use certain platforms over the internet. I mean, it is something that um is being pushed. Different people have different different views on like whether or not it's like the right approach to kind of actually solve the problem that they that they think they're trying to solve around uh protecting kids. Um and so yeah, I mean ZK it it what what is interesting to me is that like at least as far as I could tell, a lot of the the technical uh specs of a lot of these identity solutions from uh I think with particularly like the UK and Australia, I know, had some, and I think the US is working on something. But um these these identity solutions don't include ZK, as far as I know. Um which is interesting, because you would you would think that, you know, um if if you actually wanted to solve the actual problem that they say that they're trying to solve while also not causing any externalities, aka creating a giant honeypot of people's data in someone's databases, like then zero zero knowledge proof should be like your first that should be like one of the first things you should be considering, you know, right? Right?

SPEAKER_01 28:55

Yeah, so I yeah, so like we are pushing like the vacay public to the traditional world or like the the mainstream to make people aware of that and then like uh to use to use it. Since like in vaccine, like you don't need to trust anyone, like you just uh trust the math, and the math like you can do it by yourself. And we are not creating like a honey part like for uh for the hackers to hack. They are just the vicate proofs, and they keep proofs are like due to the nice properties of vaccine, you basically cannot get anything out of like of the kid proofs there. Yeah, it's it's like more reliable, more transparent, I would say, like compared with the current solution. Yeah.

SPEAKER_00 29:40

Yeah, right. Um so yeah, I don't know. Call I I think it's like we're at we're at a really funny stage in in politics almost where like you know, it's like call call your senator and teach them about zero knowledge proofs. Because what they're proposing right now in this legislation like is not is not privacy preserving at all. It like really highly highly depends on uh you know someone to build a database that is like just going to get hacked. It's not a matter of if, it's a matter of when, you know.

SPEAKER_01 30:14

Yeah. Yeah, it's just a matter of time to to hack this kind of database. Yeah.

unknown 30:20

Yeah.

SPEAKER_00 30:21

Go go to your capital and teach your uh government officials a little bit of math, a little bit of uh zero knowledge cryptography. Um yeah, thanks, Leo. Is there any are there any other uh last things that you wanted to mention before we close it off?

SPEAKER_01 30:36

Something like we uh we also want to mention is like we open source like the DKVM uh uh code repository, like you can try it out, and we have a lot of like products on on SciSec. Uh you can just check out like SciSec uh XYZ for like uh for products and then you can follow us on Twitter, like it's uh CYSIC-uh XYZ to for the latest updates like from our team. Yeah, so we have a lot of like interesting products ongoing.

SPEAKER_00 31:10

Cool. And how how can can people right now today be able to join the network to be able to make a bit of money off of their hardware?

SPEAKER_01 31:18

Yes, yes, it's like total uh permissionless. Like you can use your like uh even if you don't have a very powerful server, you can always use your laptop or even your cell phone to join, you can download like my Sec app on your whether it's like Apple or like Android phone, you can always try it out.

SPEAKER_00 31:36

Cool, great. Well, thanks, Leo, so much for coming on and appreciate you explaining Zero Knowledge Proofs to us and sharing about Seic.

SPEAKER_01 31:44

Thanks a lot. Thanks enough for having me here. Yeah, I had a very nice conversation. Yeah.

SPEAKER_00 31:50

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