Major Partner Reveal as MyEtherWallet (MEW), AnChain.AI and Others Join New Era of Fast, Scalable Blockchain Privacy

TL;DR

COTI Testnet is now live with Garbled Circuits and MPC capabilities.

Launch partners MyEtherWallet (MEW) and AnChain.ai, among others, to join COTI ecosystem.

Benchmarking study reveals COTI GC technology runs faster and lighter than other privacy solutions available.

New developer tools include Testnet explorer, faucet, and SDK support.

Affordable, scalable privacy opens the door to innovation across DeFi, AI, Compliance, Identity, DePIN and more.

We’re thrilled to announce the launch of the COTI Testnet, signalling a major milestone for affordable and scalable privacy solutions in Web3. Our launch coincides with the reveal of a sizable cohort of launch partners, including MyEtherWallet (MEW), AI-powered cybersecurity firm AnChain, and more. The new partner cohort will join companies such as Civic, Xctuality and PriveX that are already exploring COTI’s privacy Layer 2.

These partnerships underscore the recognition of privacy as a critical component in the evolution of blockchain technology across a broad swathe of sectors including DeFi, AI, RWAs, gaming, and more.

Our journey to this point has been nothing short of exhilarating. Just four months ago, we launched the COTI Developer Network (DevNet), which marked the first time developers could experiment with the groundbreaking Garbled Circuits technology — developed in collaboration with Soda Labs — for use on the blockchain. Since then the response has been astounding, with projects and developers from a wide range of sectors across Web3 joining our builders community.

Introducing The COTI Testnet

COTI’s Testnet is now live, opening up a world of new possibilities for privacy-preserving blockchain applications. There’s never been a more exciting time to get involved! Our privacy-preserving Layer 2 offers groundbreaking features that set the stage for a new era of blockchain privacy — though it maintains a familiar and robust environment for developers wishing to test and building privacy-focused applications.

Let’s take a closer look at the key innovation powering our Testnet.

COTI’s Garbled Circuits

At the core of COTI’s privacy-preserving technology is a new implementation of Garbled Circuits (GC) that allows for secure multi-party computation (MPC), enabling parties to jointly compute functions over their private inputs without revealing those inputs to each other. This technology forms the backbone of COTI’s ability to process confidential transactions at scale.

Benchmarking Shows COTI Runs Faster and Lighter

Earlier today we revealed our first benchmarking study to substantiate our claims that COTI runs faster and lighter than existing privacy solutions. Other similar privacy solutions that offer MPC have struggled to gain widespread adoption due to large computation load and cost. Our study compares the performance of Garbled Circuits (GC) to the key privacy protocol known as Fully Homomorphic Encryption (FHE) with positive results.

COTI is more performant by a clear margin, in fact it’s faster than we thought, 1800–3000 times faster! COTI is setting new standards for blazingly fast confidential computation. By providing affordable and scalable privacy, we’re opening up possibilities for applications previously deemed impractical due to performance constraints.

Tools to Supercharge Your Development on COTI Testnet

At COTI, we believe that great technology is only as good as the tools available to harness it.

We’ve ensured seamless integration with your favorite Ethereum tools and infrastructure. This compatibility means you can leverage existing development skills while benefiting from COTI’s advanced privacy features. Both new and seasoned Ethereum developers will find a familiar environment to build privacy-preserving applications.

Here’s what you can expect from our new developer toolkit:

Testnet Explorer: Easily track blocks and transactions

Uptime Dashboard: Clearly track the liveliness of the testnet

Testnet Faucet: Obtain testnet tokens to fuel your experiments

Testnet SDK support: Seamlessly integrate COTI features into your apps with TypeScript and Python.

COTI Developer Sandbox (DevNet only): A safe space to try out and learn about on-chain permission management and on-chain computation.

COTI Remix Plugin (DevNet only): Streamline your smart contract development in Remix IDE.

Each of these tools has been carefully crafted to support different aspects of the development process, from initial experimentation to deployment and monitoring.

Start building on COTI Testnet Today!

Partners Unlocking New Privacy-Powered Use Cases with COTI

COTI’s privacy chain has attracted partnerships from a broad spectrum of sectors including DeFi, AI, Security and Compliance, NFTs, Real World Assets and more.

‘ The response has been astounding’, said COTI CEO, Shahaf Bar-Geffen, ‘ with projects and developers from various sectors across Web3 joining our community to build a private blockchain future.’

We’re not the only ones excited about the potential of COTI. Fourteen new partners have joined us including long-standing wallet solution My Ether Wallet (MEW), AI-powered cybersecurity firm AnChain.ai, leading decentralized web browser Carbon Browser, cross-chain infrastructure provider Dojima, Web3 gaming company UNKJD, Ethereum name service provider ZNS, as well as Kapa.ai, Staking Rewards, BizThon, L2Beat, Privacy Guardians, Poolz and finally Gitcoin and blockchain security auditor Hacken for support on grants.

Kosala Hemachandra, CEO and Founder of MyEtherWallet commented, ‘ We are excited to collaborate together to bring COTI to user-friendly products that are open source and privacy-centric.’

We welcome all our new partners and look forward to exploring new privacy use cases and applications over the coming months, as well as revealing more details of our grants program.

The new partner cohort joins existing COTI ecosystem members: Civic, building Dynamic DID, Porta, exploring private smart wallets, Xctuality, enabling privacy in the phygital ecosystem, and PriveX, bringing privacy to DeFi perpetuals trading among others. We’re also building for Bank of Israel (BoI), the only blockchain network to be invited to participate in the BoI’s CBDC design challenge.

But that’s just the beginning. COTI’s breakthrough in scalable privacy opens doors to a wide range of use cases that were previously impractical or impossible to implement on public blockchains.

Confidential DeFi: Create private AMMs, lending protocols, and trading platforms that protect user strategies and positions.

CBDCs and stablecoins: Enable privacy-preserving central bank digital currencies that comply with regulatory requirements.

Dynamic Decentralized Identity (DyDID): Build privacy-first identity verification and management solutions.

Quantum-resistant privacy: Implement advanced cryptography designed to maintain privacy even in a post-quantum computing era.

The potential applications of COTI extend far beyond this list to cutting-edge fields such as confidential machine learning and on-chain sensitive data management. As more developers and enterprises explore the capabilities of our platform, we expect even more innovative solutions that push the boundaries of what’s possible in blockchain privacy.

We’re excited to see how the community will leverage COTI to address real-world challenges and create new opportunities in the onchain economy.

Join the Future of Web3 Privacy

The Testnet launch is a crucial step towards our mainnet deployment. In the coming weeks, we’ll be working closely with our community of developers and partner projects to refine and enhance the platform based on your feedback.

Developers, we invite you to dive in, explore the COTI Testnet, play with our new tools, and help shape the future of privacy-preserving blockchain technology. Your input is invaluable as we work towards creating a more private, secure, and efficient blockchain ecosystem.

The COTI Testnet launch is a massive technical milestone for us and the beginning of a new era in blockchain privacy. With your help, we’re unlocking new possibilities across multiple industries and use cases.

We can’t wait to see what you’ll build on COTI!

For all of our updates and to join the conversation, be sure to check out our channels:

Website: https://coti.io/

X: https://twitter.com/COTInetwork

YouTube: https://www.youtube.com/channel/UCl-2YzhaPnouvBtotKuM4DA

Telegram: https://t.me/COTInetwork

Discord: https://discord.gg/9tq6CP6XrT

GitHub: https://github.com/coti-io

COTI-2 Leading the Way in Privacy-Preserving Blockchain Solutions — Benchmark Study.

As blockchain technology evolves, protecting one’s privacy has become increasingly important. COTI-2 is expected to redefine the standards for privacy-preserving blockchain technology due to the growing need for scalable, secure, and efficient blockchain solutions.

Privacy and blockchain

Traditional blockchain systems often struggle to balance transparency and privacy, leaving sensitive data vulnerable. The result has been the development of a wide range of privacy-enhancing technologies, each with its own strengths and limitations. There have been a number of approaches developed in recent years to address this critical issue, including Zero-Knowledge Proofs (ZKP), Fully Homomorphic Encryption (FHE), and Multi-Party Computation (MPC).

COTI-2, in collaboration with Soda Labs, is at the leading edge of this technological revolution, featuring a Garbled Circuit (GC) technology that offers unmatched performance and scalability. In terms of privacy-preserving blockchain operations, the GC technology, deployed by the COTI-2 network, can be shown to outperform its competitors with impressive performance benchmarks.

Integrated functionality

There is much more to COTI-2 than basic cryptographic operations. Whether it’s simple arithmetic or complex financial transactions, the innovation of Garbled Circuits, demonstrated here, delivers consistent and impressive results. Meaning COTI-2 is not only a privacy solution, but also a platform for building secure, decentralized applications.

A Practical Approach to Privacy

COTI-2 effectively overcomes the practical challenges that arise when adopting privacy-preserving technologies. By significantly reducing resource requirements and enhancing computational speed, COTI-2 makes privacy-preserving blockchain solutions accessible to a broader range of devices and use cases.

Performance Benchmarks

The performance benchmarks for Garbled Circuits deployed in COTI-2 demonstrate impressive execution times for a variety of operations:

Operation Consistency

In the following section, we will report on GC performance data. The data can be used to directly demonstrate the performance of COTI-2. Most operations are consistent across bit lengths:

From 8 to 64 bits, the execution time of ADD, AND, OR, and XOR is nearly constant (with variations typically less than 10%).

- EQUAL, GREATER THAN, LESS THAN: Shows minimal variations (for almost all bit lengths) — usually within 15%.

Consistency (regardless of data size) enables predictable performance.

Complex operations scalability

The scaling of complex operations tends to be sub-linear despite larger bit lengths increasing execution times:

- MULTIPLY: Increases from 53,810 μs (8-bit) to 233,843 μs (64-bit), roughly a 4.3x increase for an 8x increase in bit length.- DIVIDE: Scales from 55,348 μs (8-bit) to 573,018 μs (64-bit), about a 10.4x increase.

In this case, the sub-linear scaling indicates that large data sets can be handled efficiently.

Analyzing throughput

The throughput of various operations can be calculated as follows:

- ADD (64-bit): 20,238 operations per second (1000 operations / 49,411 μs)- MULTIPLY (64-bit): 4,276 operations per second

Efficiency Ratio

We can calculate efficiency ratios by comparing complex operations to basic ones:

- MULTIPLY to ADD ratio (64-bit): 233,843 / 49,411 ≈ 4.73- DIVIDE to ADD ratio (64-bit): 573,018 / 49,411 ≈ 11.60

Compared to basic operations, these ratios are relatively low, indicating that complex operations are handled efficiently.

Onboarding and Offboarding Overhead

Despite being more time-consuming, the onboarding and offboarding processes perform consistently for all bit lengths:

- ONBOARD: Average of 287,695 μs for all bit lengths- OFFBOARD: Average of 279,759 μs for all bit lengths

Resource allocation and system planning benefit from this consistency.

Comparative Performance Index

If we consider the ADD operation at 64-bit as a baseline (46,862 μs), we can create a performance index:

- ADD (64-bit): 1.05 (minimal overhead for larger bit sizes)- MULTIPLY (64-bit): 4.99 (efficient scaling for complex operations)- DIVIDE (64-bit): 12.23 (more intensive but still manageable)

These indices provide a quick way to compare operation complexities.

GC vs. TFHE-rs

TFHE-rs is a prominent FHE library, so it’s a good benchmark for comparison:

1. Addition (64-bit):

- GC: 49,411 μs for 1000 operations (≈ 49.4 μs per operation)- TFHE-rs: 150,000 μs for a single operationGC is approximately 3,035 times faster for this operation.

2. Multiplication (64-bit):

- GC: 233,843 μs for 1000 operations (≈ 233.8 μs per operation)- TFHE-rs: 425,000 μs for a single operationGC is about 1,818 times faster for multiplication.

3. Comparison (64-bit):

- GC (GREATER THAN): 43,905 μs for 1000 operations (≈ 43.9 μs per operation)- TFHE-rs: 116,000 μs for a single operationGC is roughly 2,642 times faster for comparison operations.

GC vs. Secret-Sharing based MPC Solutions

MPC solutions differ in specific benchmarks, but there are some general comparisons we can make:

Latency: GC demonstrates low latency, which is crucial for real-time applications.

Scalability: GC shows consistent performance across different bit lengths for most operations.

Complex Operations: GCs DIVIDE operation (64-bit) takes about 573 μs per operation. Complex operations in MPC often require multiple rounds of communication, leading to higher latencies.

Taking a technological approach

The data above demonstrates that the GC technology deployed by COTI-2 has several advantages:

Faster computation: COTI-2 offers between 1,800x and 3,000x speed increase over comparable privacy solutions, depending on the type of computation required.

COTI-2 ciphertext has a size of only 32 bytes, resulting in a much smaller storage requirement than Fully Homomorphic Encryption (FHE) (with ciphertexts of at least 8KB) .

Usability and versatility

There are several performance improvements enabled by COTI-2:

Multi-device compatibility

Enhanced user experience, as compared to alternative privacy solutions

Reduced computational requirements, opening the door to broader adoption.

Compared to other approaches

A ZKP-based solution offers strong privacy, but lacks expressivity for calculating shared private states. The garbled circuits solution used by COTI-2 provides more flexibility.

Privacy and practicality are significantly better balanced with COTI-2’s approach.

Secret-sharing based MPC solutions: Although powerful, secret-sharing based MPC solutions can be performance-limited due to larger rounds of communication.

Overall Performance Advantages

Consistency: In contrast to FHE or Secret-sharing based MPC, GC, deployed by COTI-2, maintains relatively stable performance across different bit lengths.

Speed: GC consistently performs basic operations in microseconds, whereas many competitors operate in milliseconds or seconds.

Scalability: Compared to many existing solutions, COTI-2’s performance scales sub-linearly with bit length.

Storage Efficiency: COTI-2’s ciphertext size of 32 bytes offers significant advantages over FHE solutions with much larger ciphertext sizes. With a reduction in resource intensity, GC may be more practical for deployment on a wider range of devices than FHE solutions with high resource demands.

Summary

Based on these comparisons the GC technology deployed by COTI-2 is clearly more efficient than existing privacy-preserving technologies. GC gives COTI-2 the ability to perform complex operations orders of magnitude faster than current FHE solutions, while maintaining strong privacy guarantees, creating a game-changing technology in the blockchain privacy space. By combining speed, efficiency, and scalability, privacy-preserving computation in blockchain applications overcomes many practical limitations.

Conclusion

This study shows that the performance times of GC, as deployed by COTI-2, demonstrating that this privacy-preserving technology is well suited to meet the growing demand in Web3 for scalability and efficiency. COTI-2 performance benchmarks show significant improvements over its competitors. The performance of COTI-2 is consistent across all operations, even for complex ones like MULTIPLY and DIVIDE. There is no existing privacy-preserving solution that can match this level of performance, which operates in the millisecond to second range typically.

Combined with speed, consistency across bit lengths, and the ability to efficiently perform complex operations, COTI-2 can be a game-changer for privacy-preserving blockchain applications, enabling encrypted computation at an unprecedented scale and speed, opening up new applications and use cases for blockchain.

For all of our updates and to join the conversation, be sure to check out our channels:

Website: https://coti.io/

X: https://twitter.com/COTInetwork

YouTube: https://www.youtube.com/channel/UCl-2YzhaPnouvBtotKuM4DA

Telegram: https://t.me/COTInetwork

Discord: https://discord.gg/9tq6CP6XrT

GitHub: https://github.com/coti-io

COTI-2 Leading the Way in Privacy-Preserving Blockchain Solutions — Benchmark Study. was originally published in COTI on Medium, where people are continuing the conversation by highlighting and responding to this story.

Garbled circuits offer a lightweight, secure, and fast means of carrying out confidential transactions of all kinds over a public blockchain — a prerequisite for large-scale business adoption of crypto technologies.

Privacy has always been important in the crypto world. Bitcoin arose from the cypherpunk movement, and its earliest advocates were libertarians who were concerned about the threat of financial and online surveillance.

However, in the fast-moving field of Web3, privacy solutions haven’t always kept pace with the wider advance of blockchain technology. The transparency of public blockchains has made it challenging to maintain robust privacy for anything but the simplest of token transfers. With the rise of decentralized finance (DeFi) and broader Web3 applications, a more comprehensive approach is needed that protects all kinds of transactions from the attention of malicious parties.

Today’s blockchain platforms are plagued with a series of problems that arise as an unintended consequence of their transparency, including MEV and spear-phishing. It’s vital that changes if blockchain is to fulfill its potential and become the infrastructure for tomorrow’s financial and online services.

The implementation of garbled circuits (GC) pioneered by Dr. Avishay Yanai and Dr. Meital Levy and the team at Soda Labs, in partnership with COTI, offer a powerful means of encrypting on-chain operations, ensuring they are concealed from unwanted onlookers while remaining fully auditable to approved parties. The speed and efficiency of GC over other privacy solutions makes large-scale decentralized confidential computing (DeCC) a reality for the first time, and opens the door to meaningful business adoption of blockchain technology.

Why Is Privacy Important?

Transparency is a core feature of public blockchains, and part of crypto’s unique value proposition. The transparency of the blockchain means that transactions can be monitored and audited by anyone, in real-time, providing a high degree of trust in comparison to opaque Web2 systems. For example, anyone can view the Bitcoin blockchain to check the number of bitcoins in existence.

However, this transparency comes with serious drawbacks. By default, transactions can be seen by everyone. In the DeFi space as it currently exists, this leads to a number of abuses. Because transactions are visible in the mempool (a temporary holding area where new transactions wait to be confirmed), other users can see them and potentially profit from them by ensuring their own transactions are executed first. Large trades may be front-run, or auctions exploited. This problem is known as maximal extractable value (MEV), and costs Ethereum users alone billions of dollars every year.

The blockchain’s transparency also means users can often be identified. This leads to spear-phishing attempts — targeted attacks on businesses and individuals — and even physical threats.

For business applications, confidentiality isn’t just desirable: it is a legal obligation. Data protection laws like GDPR require that organizations protect their users’ personal information. Even aside from this, it is unacceptable that financial and personal information could be publicly available. Not only does this raise the risk of fraud and theft, but it would put businesses at a competitive disadvantage if other organizations could see who they were transacting with.

Confidentiality is therefore a non-negotiable requirement for businesses. However, the combination of private transactions on a public blockchain offers many benefits.

From Privacy Coins To Confidential Computing

Many of Bitcoin’s earliest users were attracted by its perceived anonymity. In practice, the transparency of the blockchain means that it’s often possible to deduce information about the parties to a transaction. A number of privacy-centric coins arose to fill this niche.

The launch of Ethereum and other smart contract platforms introduced the idea of decentralized applications and the new realm of decentralized finance (DeFi). Now, it wasn’t just simple coin transfers that needed to be shielded from outside attention, but complex transactions of all kinds.

Ethereum mainnet, as well as other smart contract platforms and L2 solutions, are fully transparent and therefore vulnerable to MEV attacks and other exploits. Business adoption of crypto technologies is hamstrung by the lack of a confidential blockchain solution. For practical and regulatory reasons, this issue must be solved to unlock blockchain’s full potential. This is the purpose of the new field of Decentralized Confidential Computing (DeCC).

DeCC: The Story So Far

Several different technical approaches have been used to develop DeCC platforms, including:

Fully Homomorphic Encryption (FHE): is an instance of an asymmetric-key encryption scheme that produces a ciphertexts in a particular form that preserves their structure even after computation. The ciphertexts can only be viewed by approved users who hold the decryption keys.

Trusted Execution Environments (TEEs): a secure area within a hardware device, which is used to execute sensitive operations. This aims to ensure that private data and smart contracts are never exposed to external threats.

Zero-Knowledge (ZK) proofs: cryptographic protocols that allow a party to prove the validity of a statement to another party without revealing any underlying information, enhancing the privacy and security of transactions.

Each of these approaches has advantages and disadvantages. FHE, for example, is a flexible and powerful technology that ensures sensitive data remains encrypted, even when operations are being carried out on it. Unfortunately, though, while any solution that entails processing of encrypted data has significant overheads, FHE entails particularly large computational costs and storage requirements, throttling the capacity of on-chain FHE solutions. A recent technical overview estimated that “running FHE on CPU is at least a million times slower than the corresponding unencrypted program”. One solution to this is to employ hardware acceleration (effectively ASIC mining for FHE), but this simply pushes the computational costs one step further out, rather than eliminating them altogether.

The chief issue with TEEs is in the name: users have to trust that these secure enclaves within the chips really are isolated from the outside world. However, there are multiple potential single points of failure along the whole supply chain for the hardware and software for TEEs, and new exploits could be catastrophic for applications that use them. Unfortunately, history shows that TEEs have not always proven as secure as the manufacturers claimed.

ZK proofs are becoming more widely used in the blockchain world, including in several Ethereum scaling solutions. However, they are not suited for applications which involve processing data from several parties. Additionally, they are complicated to work with, and can be computationally expensive (though not to the same degree as FHE systems).

Garbled Circuits: A New Approach To Privacy

While all of these technologies have been implemented by different projects, there are other solutions that offer benefits over existing confidential computing platforms. Garbling-based protocols provide one of the most promising approaches to DeCC. These were first articulated in the 1980s, but recent advances mean it is now viable to implement them on the blockchain, opening up a new arena for confidential transactions.

Garbled Circuits (GC) are the main objects used in garbling-based protocols. In brief, GC are designed for secure multi-party computation (MPC): a means of enabling multiple parties to jointly compute a function using their inputs, while keeping those inputs private from each other at every stage of the operation.

The classic example of garbled circuits is the Millionaire’s Problem, first articulated by Andrew Yao in 1982. In this problem, two people want to determine who is wealthier, but without either of them actually giving away how much money they have. Yao later developed the concept of garbled circuits to solve this problem, and his research laid the foundations for further developments in MPC.

How Do Garbled Circuits Work?

In a blog post four years ago, Ethereum co-founder Vitalik Buterin gave a technical overview of how garbled circuits work. In simplified terms:

Any mathematical function (with a few caveats) can be represented as a series of logic gates — AND, OR, NOT, XOR, etc

This function or logic “circuit” is encrypted, or “garbled”, so that the different steps that take place inside it cannot be understood from the outside

Each gate now takes one or more encrypted inputs, and gives an encrypted output

One or more users provide initial encrypted inputs

The circuit is executed, with each gate giving an encrypted output that forms one of the encrypted inputs to subsequent gates, until the process reaches the end

The circuit gives a final encrypted output — a solution to the function — which can only be decrypted by parties who have the appropriate key

Because the initial inputs, the final output, and every stage in between are encrypted, no information is leaked to the outside world at any point in the circuit’s execution

Let’s take a very simple real-world example that provides an analogy for how a garbled circuit works.

Alice and Bob want to know which of them is older, but neither want to reveal their age.

In secret, they each take a number of identical marbles, matching their age, and place them in a bag.

Next, they each put their bag of marbles on either side of a set of old-fashioned kitchen scales.

If Alice’s side is heavier, she is older. If Bob’s side is heavier, he is older. If the scales balance, they are the same age.

Alice and Bob have determined who is older, without revealing to the other how old they actually are.

In this example, the marbles (inputs) are placed in a bag (“encrypted” or “garbled”) to hide them from the other participant and from outside observers. The circuit (scales) is capable of operating with these garbled inputs, and provides a single output (one or other side is heavier).

Of course, on the blockchain, the inputs and the function computed by garbled circuits can be much more complex — making them suitable for a wide range of decentralized applications.

What Garbled Circuits Bring To The Table

Compared to other approaches to confidential blockchain solutions, garbled circuits have a number of advantages:

Lightweight. GC are computationally inexpensive, meaning they can be executed by any computer and do not require specialist hardware.

Speed. They are also extremely fast, especially compared to other solutions such as FHE — avoiding any unnecessary delays to transaction confirmations.

Secure. All sensitive information remains encrypted at every stage of the process, offering robust privacy from start to finish.

Flexibility. GC can be used to jointly compute functions with inputs from several participants.

EVM-compatible. COTI’s implementation of GC allows developers to port their smart contracts from Ethereum to COTI without modification, and add privacy features to their contracts with minimal effort.

On-chain. Their lightweight nature means garbled circuits can be executed on-chain, so no trust in third parties is required and nothing is left to chance.

Use Cases For GC

All of this means that garbled circuits are ideal for applications where confidentiality, speed, and efficiency are a priority. Just some of the use cases include:

DeFi, such as decentralized exchanges that are resistant to front-running.

Confidential token transfers. An observer could tell that a given address had interacted with a token contract, but could not tell how many tokens had been moved, to which address they had been sent, or potentially even which token was involved.

Decentralized stablecoins that can be minted without revealing the identity of the issuer, and where liquidation of collateral is not susceptible to MEV attacks.

Real-world assets (RWA) that preserve the privacy of owners and issuers, maintaining compliance in this key bridge between the TradFi and DeFi economies.

On-chain AI and machine-learning applications.

Why Do We Need Garbled Circuits?

Garbled circuits offer an effective solution to the shortcomings of existing Decentralized Confidential Computing platforms. No other technology is yet ready for the demands of large-scale DeCC.

COTI’s on-chain implementation of garbled circuits is dramatically more efficient than other DeCC solutions. Garbled circuits offer computation speeds that are over 1,000 times faster than FHE, with just 0.4% of the on-chain storage requirements. Latency — the time it takes for transactions to be communicated to the network — can be more than 100 times faster than for comparable approaches. No trusted hardware is required, either for secure processing (TEEs) or speeding up complex operations (hardware acceleration for FHE), though if desired it can be added as an extra layer of security. Additionally, GC are ideally suited to computation on shared state, giving them a critical advantage over ZK systems.

By protecting users from the unwanted implications of blockchain transparency while retaining the benefits of decentralized platforms, effective DeCC prepares the crypto sector for wider business adoption — potentially opening the door to trillions of dollars of new capital.

To find out more about garbled circuits you can discuss the latest developments in our dedicated gcEVM Vanguards Telegram group.

by guest writer, Guy B.

For all of our updates and to join the conversation, be sure to check out our channels:

Website: https://coti.io/

X: https://twitter.com/COTInetwork

YouTube: https://www.youtube.com/channel/UCl-2YzhaPnouvBtotKuM4DA

Telegram: https://t.me/COTInetwork

Discord: https://discord.gg/9tq6CP6XrT

GitHub: https://github.com/coti-io

COTI gets its very own AI Chatbot!

We are happy to share that we have now completed the trial phase of our custom AI Chatbot that can now be accessed from within the COTI developer documentation. The Chatbot runs a model that is specifically trained to serve the COTI developer community, providing tailored answers to all types of technical queries.

The COTI AI model is comprised of different sources like GitHub repositories, MPC Libraries, Docs, EVM technical docs, SDK documentation, and SDK Examples. By incorporating the broadest swathe of COTI training data, the Chatbot is able to give tailored answers on anything from onboarding and accounts to contracts and dApps. It can also tell you how to create your own privacy-preserving smart contracts!

The bot helps to speed up the onboarding process for new developers.The Chatbot will start life within the docs but plans are being made to extend it to the COTI Discord.

Ongoing Model Training

Every good AI model is continuously improving and the COTI AI model is no different. We have provided a function to allow for user feedback. Simply ask it a question about the COTI network and it will give you the opportunity to provide feedback on what it did well. The more feedback you supply, the better it gets!

So what are you waiting for? Visit our docs to give it a try today.

For all of our updates and to join the conversation, be sure to check out our channels:

Website: https://coti.io/

X: https://twitter.com/COTInetwork

YouTube: https://www.youtube.com/channel/UCl-2YzhaPnouvBtotKuM4DA

Telegram: https://t.me/COTInetwork

Discord: https://discord.gg/9tq6CP6XrT

GitHub: https://github.com/coti-io

PriveX is the first intent-based perpetuals DEX to launch on COTI, bringing unprecedented privacy and security to DeFi traders.

COTI, the leading provider of the fastest and lightest confidentiality layer on Ethereum, is proud to announce its strategic partnership with PriveX, the first intent-based privacy perpetuals DEX. PriveX has integrated COTI’s cutting-edge privacy-preserving Layer 2 technology into its platform to provide secure, confidential transactions while ensuring a seamless, safe and fair trading experience.

This partnership represents a significant milestone for the decentralized finance space. By leveraging COTI’s advanced cryptographic protocol, Garbled Circuits, PriveX can offer its users the freedoms of DeFi with the efficiencies of CeFi. Traders on PriveX will be able to execute strategies without exposing sensitive data, such as stop-loss positions or trade amounts, thereby protecting their tactics from market manipulation.

COTI’s CEO Shahaf Bar-Geffen commented:“Privacy has long been a barrier to the broader adoption of decentralized finance. COTI’s state-of-the-art confidentiality layer will provide PriveX users with the security they need to trade confidently, tapping deep liquidity pools on centralized exchanges whilst enjoying the decentralized, self-custody benefits of DeFi.”

The partnership will see PriveX launching its Test-Mainnet environment for whitelisted addresses on the Base network, with plans to transition to COTI V2 when COTI moves to Mainnet later this year. Traders on PriveX will benefit from COTI’s privacy-preserving technology, which includes features like confidential trading strategies and trade amounts.

PriveX will empower the COTI community with instant access to high-leverage positions on a wide range of coins, offering up to 60x leverage and unlocking new opportunities for strategic trading. With seamless integration into the COTI network, users will enjoy fast transactions, competitive fees (on the network and on the platform), and a user-friendly interface, all designed to enhance their trading experience. PriveX itself partners with Symm.io and IntentX.io’s ‘solver solution’ to deliver CEX-like liquidity across more than 250 trading pairs.

Today’s collaboration marks a significant expansion of COTI’s privacy-centric Layer 2 technology, demonstrating its versatility across different DeFi applications. The COTI community will enjoy first-movers advantage on the PriveX DEX, accruing reward points in return for trade volume. Points will then be counted towards an airdrop when PriveX moves to COTI V2. Join the PriveX community here.

For all of our updates and to join the conversation, be sure to check out our channels:

Website: https://coti.io/

X: https://twitter.com/COTInetwork

YouTube: https://www.youtube.com/channel/UCl-2YzhaPnouvBtotKuM4DA

Telegram: https://t.me/COTInetwork

Discord: https://discord.gg/9tq6CP6XrT

GitHub: https://github.com/coti-io