In 2018, the European Union’s General Data Protection Regulation (GDPR) came into effect, causing a wave of changes to terms and conditions in your favorite applications across the globe. GDPR aims to increase people’s control and rights over their own personal information and heavily penalizes companies that infringe on these rights. Infringing on the rights of EU citizens laid out in GDPR could result in a fine of €20 million or 4% of the annual global turnover of an enterprise, so compliance is strongly incentivized. This new regulation is widely considered a major turning point in data protection and privacy rights, starting a policy diffusion of similar data protection laws across the globe. GDPR is law in every member country of the European Union and establishes a “single data market” within the EEA. Similar regulations have also been adopted in California, Chile, Japan, South Africa, Argentina, Turkey and Brazil, among others.
GDPR (as well as many of the similar regulations) involves multiple core tenets, among others setting out the principles for which personal data can be used and processed. Lawful purposes of the use of personal data and the digital rights that citizens have over their personal data. While there are many different compliance aspects of data protection regulations, such as GDPR, here are a few examples of how our technology could help your organization stay compliant:
GDPR requires organizations processing personal data to transform the data in such a way that it cannot be connected to the person it was collected from (pseudonymization). Partisia Blockchain could help an enterprise disassociate a person from their (encrypted) data, assuring such pseudonymization through the use of multiparty computation (MPC) technology. This pseudonymization can also be done in a way to allow for continuous collection of data from the same individual, if required for e.g. a longer-term study.
Furthermore, the concept of MPC also can also aid in maintaining an individual’s control over their data, as e.g. the concept of MPC secret sharing can allow for useful outputs being generated without compromising the underlying data (see Multiparty computation: The beacon of privacy solutions explained). MPC (especially combined with a blockchain) can also therefore increase the security of personal data, as the data and calculations are all run in a decentralized fashion by nodes that are all independent from each other. Partisia Blockchain’s nodes and their operators are all independent, run independent systems and have been vetted for cybersecurity by Partisia Blockchain experts.
Another right laid out by GDPR is the so-called right of access. This is the right of people to be able to see how their data is being processed and with whom it is being shared. The ledger kept on a blockchain could help an organization provide an immutable record to ensure this right. For the same reason, the blockchain could help organizations provide the record of processing activities required for GDPR-compliance under certain circumstances as well. As opposed to some other blockchains, Partisia Blockchain also allows for the possibility of private data to be removed from the record. Essentially meaning that data entered into the blockchain can be erased later on, allowing for compliance with GDPR’s right of erasure (the right for people to have their personal data removed from a database).
Lastly, the geographical location of servers used to process personal data could sometimes mean the difference between compliance and a criminal offense. Partisia Blockchain’s jurisdiction management v1.0 allows organizations’ developers to specify the geographic location of nodes to be used in calculating personal data. This could for example allow for private data from the EU to only be sent to EU-based nodes, ensuring that the integrity of the single data market and the data rights of EU-citizens are not breached.
Partisia Blockchain is committed to empowering others in solving real-world problems using our cutting-edge technology. Data rights and data privacy challenges are two of these problems.
Please contact us, if you have any questions about how our technology could enable data privacy or think we can help your organization in improving its data protection architecture.
Contact information: build@partisiablockchain.com
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The point of this document is to provide the shortest (and most intuitive) possible introduction to each of the technologies mentioned in the title. I hope I succeed in this endeavor.
The technologies in this document all — with exception of differential privacy — deal with “secure” computation on data. At a very high level, this means they can be used to perform an arbitrary computation on one or more pieces of data, while keeping this data private.
Secure multiparty computation, which is what we do here at Partisia, is the term for a fairly broad class of protocols that enable two separate entities (called parties) to compute a function, while revealing nothing except the output.
An MPC protocol typically proceeds in three phases: First the inputters secret-share their private inputs. This step can be thought of as each user sending a special type of encryption of their inputs to the nodes doing the computation. The encryption ensures, for example, that at least two out of three nodes are required to recover the input, and thus, we get a security model that relies on non-collusion. It could also be the case that all three nodes must collude to recover the input — in this case, we have a full threshold model (since all servers must collude to break privacy).
The next step involves the nodes (the servers A, B, and C) performing the computation on the encryptions (i.e., secret-shares) received in the input step.
When the nodes finish the computation, they will hold a secret-sharing of the output. Each node’s share is returned to the users, so they can recover the actual output.
As might be inferred from the figures above, MPC works particularly well if the computation nodes are well-connected. Indeed, what makes MPC expensive to run is all the data that the nodes have to send between each other.
MPC have been actively studied in academia since the early 1980s and there are a lot of good resources available to learn more about it:
Fully homomorphic encryption (FHE) solves a very old problem: Can I have my data encrypted and compute on it too? FHE is a tool that allows us to not only store data encrypted on a server, but which allows the server to compute on it as well, without having to decrypt it at any point.
A user encrypts their private data and uploads it to a server. However, unlike a traditional E2EE (End-to-End-Encrypted) scenario, the server can actually perform a computation on the user’s private data — directly on ciphertext. The result can then be decrypted by the user using their private key.
FHE, unlike MPC, relies on clever cryptographic computation, rather than clever cryptographic protocols. On the one hand, this means FHE requires less data to be sent between the server and client compared to MPC. On the other hand, FHE requires a lot of computation to be done by the server.
Practically speaking, FHE is slower than MPC (unless we have an incredibly slow network, or incredibly powerful computers).
Practical FHE is a relatively new technology that only came about in 2009. However, since then it has received quite a bit of interest, especially from “bigger” players like Microsoft or IBM.
Partisia Blockchain supports FHE solutions.
While both MPC and FHE allow us to compute anything, zero-knowledge proof (ZKP) systems allow us to compute proofs. In short, ZKP allows us to compute functions where the output is either “true” or “false”.
ZKPs are incredibly popular in the blockchain space, mainly for their role in “rollups”. The particular type of ZKPs used for rollups are ZK-SNARKs, which are succinct proofs. In a nutshell, a succinct proof is a proof whose size is some fixed (small) constant, and where verification is fast. This makes smart particularly useful for blockchains since the proof and verification are both onchain.
That said, ZK rollups don’t actually use the zero-knowledge property — they only use the soundness and succinctness properties of the proof scheme.
Soundness simply means that it is very difficult to construct a proof that appears valid, but in actuality is not.
ZKPs, like FHE, takes place between a single user and a verifier. The user has a secret and they wish to convince the verifier about some fact concerning this secret, without revealing the secret. ZKPs don’t designate a particular verifier, so anyone can usually check that a proof is correct.
The final private computation technology I will talk about here is trusted execution environments. A trusted execution environment, or TEE, is basically just a piece of hardware that is trusted to do the right thing. If we trust this particular type of hardware, then private computing is clearly doable.
TEEs, being hardware, are tightly connected to some hardware vendor. Often when TEEs are mentioned, what is really meant is something like Intel’s SGX or ARM TrustZone. SGX is the TEE used by Secret Network, for example.
The security model of TEEs is fairly different compared to the other technologies I have written about so far, in that it is a lot more opaque. Vulnerabilities have been demonstrated in different iterations of different TEE products, especially SGX.
Differential privacy is radically different from the previous technologies. (In this discussion I will exclude ZKPs since it does not allow general computations.)
While MPC, TEE and FHE all provide means of computing something on private data, they do not really care about what that something is.
For example, it is possible (albeit pointless) to compute the identity function using both MPC, TEE and FHE.
This is because MPC, TEE and FHE allow us to compute anything. In particular, they allow us to perform computations that are not really private.
At this point, we may ask: Well, why would we perform such a silly computation on private data? For some computations, it might be easy to see that it is not private (in the sense that the original input can easily be inferred from the output). However, there are many computations that are seemingly private, but which can also leak the input if we are not careful. For example, it has been shown that it is possible to extract machine learning models, simply by querying a prediction API. In another example it was shown that it is possible to extract the data that a model was trained on.
These issues all arise because there are no restrictions on the computation that is performed. Differential privacy tries to fix this.
Differential privacy is used to provide a fairly intuitive guarantee. Suppose we are given two databases A and B. The only difference between these two databases, is that a particular entry R exists in A but not in B. Differential privacy now states that, no matter which type of query we make on the database, we will not be able to guess whether we are interacting with A or B.
Naturally, this means that some queries cannot be allowed. For example, it is not possible to obtain differential privacy if one can simply ask “Is record R in the database?”. Generally, differential privacy is obtained by adding noise, or synthetic data, to the database as well as restricting the type of queries that are allowed.
What makes differential privacy different from MPC, TEE and FHE, is that differential privacy makes guarantees about the output of a computation, whereas MPC, TEE and FHE makes guarantees about the process of arriving at that output. In summary:
This also means that differential privacy is not in direct “competition” with MPC, TEE or FHE, but rather complements them.
While each technology has its specific advantages and use cases, it is our feeling that Partisia Blockchain’s MPC, backed by 35 years of research and practical implementation does seem to provide the most overall coverage of all possible scenarios with very little drawback.
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A blockchain, at its very core, is a way for everyone to agree on what the current state of the world is, without having to rely on a trusted authority.
Of course, by “everyone” we don’t actually mean everyone, but instead everyone who believes in the security model. Likewise, by “the world” we also don’t actually mean the world, but rather, whatever is currently written on the blockchain’s ledger. Nevertheless, well-known blockchains such as bitcoin or ethereum both have market caps in the 100s of billions of USD, which tells us that the technology excites people.
Programmable blockchains, in particular, are exciting because their “world” is very rich. On a programmable blockchain, the “world” is basically the current memory of a computer, and so, simply by being clever about how we design the programs that run on this computer, we can use it to accomplish almost anything.
Let’s digress for a bit and classify programs into three categories:
— Those that take a public input and produce a public output
— Those that take a private input and produce a public output
— Those that take a private input and produce a private output
A programmable blockchain such Ethereum supports programs of the first kind: Everyone sees what goes into a smart contract on Ethereum, and everyone sees what comes out again. This is great for some applications (like agreeing on who bought a NFT), but clearly not sufficient for others (like performing an auction).
Several solutions have surfaced which attempt to support the remaining two types of computations. Let’s take a brief look at some of them:
Zero-knowledge proofs (ZKPs) are, in a nutshell, a way for someone to convince (i.e., prove to) someone that they know or possess something, without revealing anything about that something. One situation where this shows up, is when someone wishes to prove to someone else that they control a certain amount of tokens.
ZKPs can therefore be used for private-public and private-private computation, to a limited degree. ZKPs can only compute, well, proofs. This in particular means that the computations are limited to a binary “yes” or “no” output. Moreover, ZKPs are inherently single-user oriented, so it is not possible to perform a computation that takes multiple private inputs.
Note that a program that takes a public input, but produces a private input does not make sense. If everyone can see the program and what goes into it, then everyone can obviously see the output as well.
Another private computation technique is fully homomorphic encryption, or FHE as it is called for short. At its very basic, FHE is a way of encrypting data such that it is possible to perform computations directly on the encryption.
This immediately tells us that FHE for sure supports private input private output type computations.
However, FHE, like ZKPs, are oriented towards a single user scenario. This means that, although FHE can perform any computation (which ZKPs cannot do), they cannot perform a computation that receives private inputs from multiple users.
In contrast to the two above technologies (as well as the next one), trusted execution environments (shortened as TEEs) are a purely hardware based solution to the private computing problem we’re looking at.
A TEE is simply a piece of hardware that have been hardened in certain ways that make it hard to break into. If we believe this to be the case, then a TEE can be used to perform the private input, public/private output computations we’re interested in.
Inputs are encrypted using a key stored only on the TEE, and computations take place on the TEE after decryption. When the computation is done, the output is encrypted (or not, depending on whether the output should be public or private) and then output by the TEE. In this way.
TEEs therefore clearly support the type of single-private-input computations talked about so far. However, the situation is a bit complicated if we want to receive inputs from multiple sources. Indeed, the only way that can be possible, is to make sure the same key is stored on everyone’s TEE.
The last tech I will look at is secure multiparty computation, or MPC. This privacy tech supports both types of computations, just like FHE and ZKPs, but where it distinguishes itself is that it naturally supports private inputs from multiple sources. Indeed, there’s a reason it’s called secure multiparty computation.
This makes MPC especially suited for a blockchain because of its multi-user nature.
The above categorization leaves out a lot of details, since it talked about neither the security models that each of the technologies use, nor about their efficiency.
Each of the four technologies above operate in a particular security model, and none of the models are exactly the same. Likewise, they each have some properties that make them desirable compared to the others. (For example, FHE requires more computation, but less communication, than MPC.)
In general, MPC does seem to come out on top, and is the only technology that easily supports computations where multiple users provide inputs. MPC, by its nature, is a decentralized technology, which is probably why it works so well in a blockchain setting. That being said, an ideal world would probably use all of the technologies in a carefully created orchestration to ensure the best guarantees in terms of both security and efficiency.
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Self-sovereign identity (SSI) is an ever increasingly important concept to enable users control over their own data and let them share it with whom they want. Today, data rests in centralized databases that belong to big enterprises with little transparency into how the data is actually being used and for what purpose.
SSI turns this around and data starts with the users, actually resting at users own device at first. Then it is up to the users to choose with whom and what data they share. Additionally, privacy-preserving features, such as selective disclosure and predicates enhance the user to share data without sharing it all or just prove simple facts about the data.
There are many great tools and infrastructures that can handle SSI, and Partisia Blockchain’s MPC technology adds a new component to the stack that enables new business models, enhances privacy for the data-driven economy, and will take your project ahead of the competition. So read on if you are a builder of the US$27 billion global digital identity market that is expected to expand at a CAGR of 17.2% from 2023 to 2030.
First things first, digital identity usually revolves around three actors: issuer, holder, and verifier.
The issuer issues verifiable credentials to the holder, and the holder can then present the credentials to a verifier who can verify the content by digital signatures and Decentralized Identifiers (DIDs) that may be on a blockchain. For most digital identity use cases, DIDs and associated DID documents are the only elements that get on the blockchain. We do not take a deep dive on this in this article.
DIDs and verifiable credentials are some of the essential components that make up digital identity, especially digital identity that works with decentralized networks. DIDs are a type of address that is generated to manage digital signatures, and verifiable credentials are credentials created and issued by any issuer based on their DIDs.
To enable real SSI, the users will have to store all data themselves at first, often in digital identity wallets, and only then will the user be in full control. The data itself can be data inputs from users such as personal Identifiable Information (PII) or digital verifiable credentials issued by a third-party, e.g. KYC provider issues KYC claim as digital verifiable credential. Credentials are often issued and exchanged by an agency that establishes secure peer wise connections.
Multiparty computation (MPC) is a groundbreaking technology that allows multiple data inputs to remain private while still being computed on and only sharing the outputs. The computing itself is carried out by specially selected MPC validator nodes who each compute on secret shares of the data and privacy is guaranteed by cryptography.
Compared to ZK proofs, such as zk-SNARKs, MPC is a game changer that allows computing on any function. This takes digital identity to the next level because it is now not only possible to share data with privacy features, but also carry out decentralized computation on private data and write business logic into private and public smart contracts to orchestrate the process and rules.
As we learned before, ZK proofs are good for simple presentations about specific data, e.g. a verifiable credential issued by an employer can be used to prove to the bank that you earn more than US$80,000 a year to qualify for a loan without revealing the exact amount you earn.
Now imagine that we need to compute statistics on multiple inputs from multiple users and compare a single person’s salary to the average, all while preserving privacy. ZK proofs cannot handle general computations on multiple inputs and comparison is limited to two users presenting against each other, so another system would have to support it. This is where Partisia Blockchain’s MPC comes to save the day! MPC on Partisia Blockchain can handle multiple inputs and preserve the privacy while carrying out efficient general computation.
Even though all smart contracts and data can be private, it is often worth considering only to push the most sensitive data and operations into private computation because it is generally more expensive than public computation. This goes for all ZK technology. For instance, if you want to calculate the average salary of employees, you might consider just the salary as private inputs plus pseudonymized identity, and then do statistical calculations in the public space.
When we look at DID/SSI solutions, the business requirements of the implementation usually go past simple verification of ID. DID/SSI proof is just the first step. The real challenge is what other data do you need after the verification. Perhaps it is to verify that this person has proper credentials for accessing a system. Or another popular use case for DID is to verify a user has enough assets to pay for something without revealing their total asset holding. Another app that is looking to build on our system is trying to create a persona on-chain, which advertisers can target, without revealing personal information about the user themselves.
In all these use cases, a simple proof system becomes too expensive and slow due to the fact that each individual parameter must require a proof. When you have 10 users, maybe this is possible. But what happens when you need to scale to 1000 or 10,000 users? And proofs are not computations. It is unable to compute the various different private data for analysis.
This is where MPC can extend the functionality of DID/SSI to create multi-functional applications. Through MPC you can both prove and compute multiple parameters in a single computation and include all the additional business requirements while keeping the data private.
During the pandemic, many attempts were made to create a Covid-19 passport so citizens could prove they were either vaccinated or tested negative while preserving privacy. Zk proofs are good for this, but limited to only presenting yes/no results to a verifier without extensive physical verification such as ID cards, which would compromise SSI principles.
In collaboration with HES-SO Valais-Wallis, Partisia Blockchain developed a solution where identification is reduced to matching an individual’s face with an image of the person’s face powered by MPC in order to increase security and privacy. The Partisia Blockchain ensures trustworthy information is broadcasted to the verifier and MPC ensures that the private information about the citizen is used only for matching and kept hidden for the verifier.
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July has brought remarkable progress and achievements to Partisia Blockchain! We are thrilled to share the latest developments in our dynamic ecosystem. In July, we unveiled our Grants Program for the second half of 2023, empowering visionary builders in the blockchain space with up to 3 million $MPC tokens. These pioneering teams will have access to cutting-edge technology and infrastructure, unlocking new possibilities in decentralized applications. Our commitment to driving innovation goes beyond financial aid — we empower those who challenge the status quo. Join us as we explore the exciting developments in our ecosystem, reflect on our impactful presence at EthCC, and delve into the tech highlights that pave the way for a more robust and user-friendly Partisia Blockchain.
Partisia Blockchain Foundation was thrilled to reveal our Grants Program for the second half of 2023, offering up to 3 million $MPC tokens (valued at US$1.2 million as of today) to pioneering builders in the blockchain space. We are seeking teams determined to create unique solutions that surpass current blockchain limitations. With our support, these projects will have access to cutting-edge technology and infrastructure to bring their groundbreaking ideas to life, addressing challenges previously considered impossible on other chains. Our commitment to driving innovation extends beyond financial aid, as we commit to empower teams that stand out and revolutionize the possibilities of decentralized applications. You can check out our value proposition and read the grant guidelines to apply now!
The Partisia Blockchain team was also thrilled to participate in EthCC conference in Paris in July, where we celebrated collaboration, strengthened partnerships, and reconnected with blockchain friends. Thanks to EthCC for providing a valuable platform for us to showcase our innovative technology, enabling secure collaboration while preserving privacy through advanced Multiparty Computation (MPC). We hope to see more of you next year.
As adoption is one of the main focuses for us, we kicked off a new adoptions team creation with a meeting in Aarhus. All the adoption officers were brought together to align on our strategy and goals for this year. Some of the key areas we agreed to focus on were in metrics, (number of leads from various sources, percentage of conversion, effective marketing campaigns, etc) to understand better where we are doing well and where we need to improve on.
Talking about adoptions, we are also happy to introduce another amazing project that has signed on to build on Partisia Blockchain. Veric is a credential and asset oracle running on Harmony One and they will begin to integrate Partisia Blockchain’s privacy technology to add additional functionality to their application. By adding the privacy layer, they aim to privatize details of their assets that they are looking to use for payment.
We were also honored to participate in this year’s University of Geneva “SDG Summer School”. The focus this year was “Open Source Health Solutions” and students from across the world met during three weeks on the ground and online. We had the pleasure of coaching a group of young minds looking to solve a technological problem for a healthcare company. The innovative solution the students came up with uses MPC and blockchain technologies and could have a positive impact on women’s health.
In line with our Ecosystem Focus, we were excited to showcase SecondLane, a groundbreaking project co-founded by key players in the Web3 OTC market. Offering advanced technology and licensing expertise, SecondLane is building on Weezi empowers project teams, advisors, and investors to unlock liquidity for unvested tokens and equity, while also facilitating the discovery and trading of illiquid digital assets. Explore SecondLane’s unique features in our guest blog, and join us for an insightful Q&A discussion with Oleg Ivanov, Co-Founder of Weezi/SecondLane, to gain exclusive insights into the platform.
As we reflect on the exciting developments in July, Partisia Blockchain has been busy pushing the boundaries of our technology and infrastructure. Here are some of the key highlights from our roadmap.
With these exciting developments, we are paving the way for a more robust and user-friendly Partisia Blockchain. As we move forward, our team is eager to reveal more groundbreaking tech updates next month. Thanks again to our community and your continued support!
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Partisia Blockchain Foundation is happy to announce our grants program for the second half of 2023. We are giving out up to 3 million $MPC tokens (valued at US$1.2 million from last years public sale price of 40¢ a token) to builders that want to create something unique in the blockchain space. Something that is not possible on any other chain.
Partisia Blockchain is the worlds first blockchain that combines a generic programing language to enable a customizable secure multiparty computation (sMPC) solution into an interoperable and scalable blockchain.
Unlike other privacy blockchains that do zero knowledge proof, or only a specific MPC function, Partisia Blockchain’s research based sMPC allows for customizable solutions to fit your specific needs. With features that allow for solutions to be regulatory compliant (such as GDPR, HIPAA, etc), and fully auditable, Partisia Blockchain allows for the solution to solve problems in many use cases.
Our ecosystem is full of unique real world projects that are unique in the blockchain space. From solving for MEV attacks, tackling tender corruption in the public domain, to meeting CSRD compliancy, privatizing DAO voting to ensure integrity of the vote, our partners are not building yet another same type of application in other blockchains. And this is where we want you to come in to build something unique, something not seen in the industry.
Our grant guidelines are here, but mainly we are looking for teams that really want to create a unique solution that cannot be solved in other blockchains. We provide the infrastructure and the technology to bring these solutions to life. We are looking for teams that are really looking to stand out from other dApps, or solve for a problem that is currently not possible in other blockchains.
If you already have an existing app, you dont have to port your existing app over into our blockchain to take advantage of our MPC tchnology. You can use our MPC-as-a-Service model to request the computation as a service. Our interoperability model allows for other tokens (Eth, BNB, Polygon USDC, with more to come) to be spendable as gas on our chain, allowing flexibility to existing applications to take advantage of our technology as well.
What is your unique idea? What are some of the problems you have not been able to solve in the blockchain space? Do you want to create something unique to stand out from all the other similar dApps that do the same thing?
Lets build something different together!
Stay updated:
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At present, it requires a fair amount of technology knowledge to build and support a node in PBC. While many who do not have a technology background have been able to build and maintain nodes, it still creates a barrier that many individuals or organizations feel hesitant to cross. The other challenge is the current staking and job association process. Because the staked MPC tokens in a node are being used as collateral for all the types of jobs the node is running, unstaking and unassociating tokens that are being used can be a challenge.
This is why we are putting focus on implementing a simpler node setup and operations process. This will allow easier setup of nodes as well as easier associating and dissociating of your tokens.
These new features will be rolled out in phases, with the first one being automatic node registration. A simplified registration process will be rolled out where just the configs on your node will kickstart the KYC/KYB and the registration process.
Second phase of the project will be to simplify the association and dissociation of your staked tokens. It will all be a part of our “Staking 2.0” model, which will look to make it easier and less restrictive for both node operators and delegated stakers to manage their stakes.
Running a node will still require some level of technical skill. We hope by automating some of the process, it will make it less confusing and easier for the registration process.
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As we continue to see development occurring on our blockchain, we are always on the lookout for feedback on how to improve our platform, either to make it easier for developers to develop on, or to add new functionalities to help improve the product offering by the teams developing on our chain.
In the last 6 months we’ve been listening to the developers and have been working on various new functionalities and features that should help improve the quality and functionality of the projects. Some of them came in the form of development tools which we reviewed last week.
In this article, we will review the new feature sets that are upcoming to help developers improve upon the existing features or add new functionalities.
Some of these features will also create new use cases for the MPC tokens
Improvements in the PBC as a Second Layer Functionality
One of our main value propositions is our cross-chain bridge (Hermes). This unique bridge and gas payment system allows other chains to be a usable asset in Partisia Blockchain. It is this bridge that allows other chains to call our MPC technology as a service and pay for it using their native coins. But at the moment the data that is transferred is through manual data attestation, and the transfer only occurs in one way (PBC -> EVM).
By implementing BYOC messages to be supportable, we will now implement a two way communication system. This allows for the smart contract writer to hook events that are happening in the EVM back to PBC. Through adding a MPC powered threshold key and tying our oracle servers to collateralize these data through MPC tokens, developers will now be able to create an automated bidirectional flow of data between the EVM and PBC. This opens up additional functionality, such as adding message information in NFTs and allowing them to be transferable cross chain, or sending and receiving of data during the actual bridging transfers.
Staking as an Insurance
Currently, once the funds inside a smart contract runs out, the contract gets deleted. We will be creating a new method to allow for SC owners to stake their MPC tokens as insurance to allow for these smart contracts to continue to live on even if the funds run out of the contract. This will allow for both a safety mechanism in the event funds do run out and also introduce another use for MPC tokens.
ZK Contract Lifetime Beyond 28 Days
Currently the data in a ZK contract lasts for 28 days. Going forward, we will introduce a way to allow for this data to be extendable to go past the 28 days through staking MPC tokens and re-funding the smart contract.
ZK Computation in Batches
This feature will allow for multiple ZK computations to be batchable so that you do not have to execute each and every computation one at a time.
Allow ZK Contracts to Control User Data
Currently the developers writing ZK smart contracts do not have flexible control of the Zero Knowledge data. Through this feature, we will allow for developers to have greater control of the type of data and the control of how the data will be used.
We hope that the above will both help improve the speed in which development can be done as well as allow for new features to be implementable by the developers.
As each of the items complete, we will make a separate announcement in our development channels.
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Bitcoin is what started it all. The coin that began the blockchain industry and even over 14 years after its initial creation, and after so many new coins trying to improve upon the original, it still stands as the king of crypto currency. It is still the main form used as payment in the blockchain industry and others are either built as bringing functionality more than being a currency or is relegated as 2nd place at best.
As mentioned in our interoperability article, the current blockchain L1 ecosystem are basically in a zero sum game. Every chain is trying to be faster, cheaper, more secure and easier to build on. And each blockchain operates by using their own native coin for their transaction fees. And as DeFi came into the picture, DEX’s began looking for options to allow for swapping between chains that were not native to itself. Enter wrapped tokens.
Currently in the DeFi ecosystem, there is only one way to trade BTC. By creating a wrapped version of itself. Whether its wBTC, HBTC or renBTC, etc, it is basically all a similar form of custodying a BTC and minting an IOU type mirror token on the native network. When the smart contract holding the mirror coin is burned, then the locked, or custodied real bitcoin is released. One of the problem in this system is that you must give trust to the custodians. Not only does this go against the trustless-system ethos of public blockchains, if something happens to the custodians (hack, out of business, etc) then your wrapped tokens could be lost or become worthless.
While Partisia Blockchain can implement wrapped bitcoin as BYOC asset easily, this fundamental architecture of wrapped bitcoin tied to a custody goes against the principles of allowing native coins to be used as a form of transaction payment in the blockchain. As mentioned above, from price parity between real and wrapped BTC, to security issues raised by using a custodian (corruption or even worse, a hack in the custody system) there were too many compromises. And so we are taking the road less traveled and working toward finding a solution to allow for native bitcoin to be usable as an asset in the Partisia Blockchain.
This means we are creating a multi-phase program to build this road. The first phase will be a research phase. We’ve already begun this effort and hope to complete it in the next few months. Once the research is complete, we will know the effort needed and then will engage in an architecture and engineering sessions to plan out the work to accomplish this.
This has some major possible benefits. From allowing users to spend native BTC as gas transactions for applications built on the Partisia Blockchain, to creating a native token swap between BTC and another BYOC chain, or even helping to scale transactions in the bitcoin network, implementing native BTC directly in the Partisia Blockchain network will open up new possibilities in the blockchain industry as a whole.
Please be on the lookout for future news of the results of this research.
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