What could they enable for Blockchain privacy?

Blockchains were originally designed to be transparent, with all wallets and transactions on public display. Many followers see this “distrust” as a strength, but there are some obvious drawbacks, such as the security risk of having all of your financial activity available on-chain.

We can see this in the rates of illicit activity around blockchain, with bad actors accounting for $39.6 billion in transaction volume by 2022.

We are also seeing a growing leadership tactic for personal gain, where users with the technical skills to do so reorder trades before they commit to a block. In this way, they can ensure that their own operations are always profitable.

These are just two examples of why transparency is often seen as a mistake, and it’s also why blockchain privacy research is heating up. We are now seeing a flurry of innovation within the ecosystem to drive privacy solutions, possibly the last frontier for blockchain.

Blockchain Privacy Solutions

You may already be familiar with zero-knowledge proofs, or ZKP, one of the first blockchain privacy solutions to gain widespread adoption. ZKPs allow data sharing between two parties without revealing any sensitive information. However, they fall short when handling more complex calculations.

In many cases, blockchain applications need multiple parties to compute solutions together, known as Multi Party Computation (MPC). This is where fully homomorphic encryption (FHE) came into play. About four years ago, FHE emerged as an elegant solution to solve the MPC problem. FHE allows multiple parties to perform computations on encrypted data without needing to reveal or know the underlying data points in order to retrieve the final result. However, FHE faces significant scaling issues given its high IT costs.

Fuzzy circuits, lightweight and high-speed Blockchain privacy

Garbled Circuits, a technology developed by Soda Labs and exclusively implemented by COTI, aims to solve the MPC problem with much lower implementation costs and much better performance.

In essence, fuzzy circuits can be used to perform confidential multi-part computations of varying complexity with any number of participants providing input. This makes it suitable for complex applications in blockchain protocols, including private smart contracts. However, tweaks to the technology today make it less computationally intensive, allowing it to scale.

How do fuzzy circuits work?

The concept of fuzzy circuits dates back to the late 1980s, when it was proposed as a solution to Yao’s millionaire problem by the famous cryptographer Andrew Yao. Imagine that there are two millionaires, Alice and Bob, who want to know who among them has more money. The problem is, no one wants to reveal exactly how much they have. Instead of revealing how much money each of them has, they can settle their dispute with the help of Confused Circuits.

Alice and Bob each write their net worth in ciphertext, as a string of letters and numbers. They both put that paper into a black box, and after a split second, a piece of paper with the name of the richest person is ejected. In this example, the black box is the Garbled Circuit, a powerful computer program that can perform complex calculations on encrypted data without leaking any information.

Fuzzy circuits introduce new levels of confidentiality to Web3, protecting data and metadata to enable confidential payments, private/blind auctions, and secure on-chain management of sensitive information without sacrificing performance. COTI has demonstrated the effectiveness of the technology ahead of its integration with the Ethereum-based Layer-2 network, COTI V2, which was launched in April.

Web3 use cases for fuzzy circuits

As blockchain applications grow more complex, there is a need for a privacy solution that can handle secure MPC without any limit to the number of entries. In such cases, fuzzy circuits have great potential.

Confidential DeFI: Fuzzy circuits enable confidential transactions, allowing decentralized finance (DeFi) applications to maintain regulatory requirements while solving MEV losses by encrypting transaction data, protecting it from sandwich bots. Just a few of GC’s DeFi use cases include private automated market makers (AMMs), collateral-less lending, dark pools, and hybrid exchanges. These can leverage both centralized and decentralized elements while maintaining the confidentiality of business details.

Dynamic Decentralized Identification (DID): Fuzzy circuits facilitate identity verification and the exchange, computation and storage of personal information without revealing real data to other parties, ensuring KYC compliance and maintaining the privacy of the ‘user. For example, decentralized lenders can now establish someone’s eligibility for a loan without the individual exposing their wallet address or personal information. GC advancement preserves privacy while meeting regulatory requirements.

On-chain sensitive data management: Fuzzy circuits enable the storage of encrypted data on-chain, enabling the analysis of sensitive information without compromising privacy. Data can be securely shared between sites, preventing companies from scraping and selling it. Some of the applications made possible include confidential on-chain voting systems and healthcare services. By storing encrypted data on-chain, GC meets strict data protection standards while offering the benefits of blockchain data storage and analysis.

One of the main characteristics of fuzzy circuits is their efficiency. Benchmark tests have shown that fuzzy circuits are much faster, lighter, and more cost-effective than any other privacy-preserving technology currently available. This makes GC highly scalable, ensuring the technology can grow alongside expanding markets such as real world assets (RWA) and artificial intelligence (AI).

Confidential transactions for payments, Stablecoins and RWA. Garbled Circuits maintains fund flow transparency while encrypting transaction details, ensuring regulatory compliance for payments, stablecoins and real-world assets (RWA). RWAs include assets such as real estate, commodities and securities that require high levels of privacy. The ability of GCs to ensure privacy, meet regulatory requirements, improve security and scale efficiently makes them an ideal choice.

Machine learning and confidential AI. Garbled Circuits also enables private and secure interactions with AI and Large Language Models (LLMs), safeguarding the confidentiality of data models and the privacy of data sources as required by law. The GC can be used to enable decentralized and democratic ML model development and opens up new possibilities for privacy-focused data markets that allow researchers and companies to work with datasets without exposing sensitive information.

Summary

In short, Garbled Circuits is revolutionizing privacy in blockchain applications, offering solutions that fit across sectors including DeFi, identity management, sensitive data handling, and AI. With its increased performance and scalability over other privacy solutions such as FHE, Garbled Circuits will play a critical role in the future of Web3.

Author: Shafah Ban-Geffen, COTI CEO and Co-Founder

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