Privacy is all relative. The degree of privacy you would expect in your own home is significantly higher than that you would demand in the mall, for example. And in the digital domain, the privacy you would expect when banking is higher than the level you would expect when, say streaming a movie. Thus when it comes to determining the parts of your identity you’re willing and unwilling to share, context is important.
This is particularly true in web3, where many of the activities you conduct onchain don’t require iron-clad privacy protection. Playing a web3 game or minting an NFT, for instance, are tasks that most users aren’t particularly concerned about obfuscating. But other things – entrusting your KYC data to a DeFi platform or paying an employee without revealing your wallet balance – are areas where privacy is desirable. And right now, the onchain landscape is poorly served in this regard.
The technology to support selective privacy while maintaining compliance is out there. It’s just not been implemented yet into every major web3 wallet, dapp, and network. But make no mistake, that time is coming now that privacy is back on the menu and being demanded not just by retail users but institutions too. And the latest wave of privacy technologies is capable of satisfying all parties – including those ever-watchful regulators.
If there’s one privacy tech on this list you’ve heard of, it’s almost certainly zero-knowledge proofs (ZKP). They stand as a foundational pillar in onchain privacy, allowing one party to prove the validity of a statement to another without disclosing any additional information. For instance, in decentralized finance, ZKPs enable private transactions where users can transfer assets without revealing amounts or identities, mitigating front-running and surveillance risks.
Beyond DeFi, the tech supports verifiable credentials in identity systems, where individuals prove attributes like age or qualifications without exposing full profiles, reducing the likelihood of data breaches since user data doesn’t need to be stored on centralized servers. The benefits of ZKPs extend to scalability too: by compressing data, they enable Layer 2 solutions to process thousands of transactions privately yet verifiably.
Projects such as Midnight Network – the Cardano sidechain – are taking full advantage of these properties, using ZKPs to shield commercial and user metadata in dapps. This enables regulatory-friendly privacy that protects sensitive information without compromising auditability. This selective disclosure approach to privacy not only bolsters security but aligns with evolving global data protection standards, making ZKPs a gateway for greater institutional adoption.
While ZKPs excel in verification, they are complemented by Fully Homomorphic Encryption (FHE), which addresses a different facet of privacy: performing computations directly on encrypted data. FHE allows operations such as addition or multiplication on ciphertexts, yielding encrypted results that, when decrypted, match what would occur on plaintext. This seeming alchemy of encryption, rooted in lattice-based cryptography, eliminates the need to decrypt data during processing, thereby preventing exposure even on environments such as public blockchains.
In web3, FHE unlocks use cases in confidential machine learning, where models can train on encrypted datasets from multiple sources such as healthcare providers sharing patient data for AI-driven diagnostics without revealing individual records. Similarly, in supply chain management, FHE enables aggregated analytics on proprietary inventory data across partners, preserving that all-important competitive edge while optimizing logistics.
The primary benefits of FHE include robust security against quantum threats and seamless integration with existing smart contracts, albeit with the aid of optimizations to counter computational overhead. Zama, arguably the best-known blockchain project developing FHE-based solutions, has demonstrated this through open-source libraries that accelerate onchain FHE by orders of magnitude. This paves the way for privacy-enhanced AI and blockchain applications that gain all the benefits of privacy and none of the downsides. By enabling “always-encrypted” workflows, FHE extends privacy from static storage to dynamic computation, bridging gaps left by proof-based systems.
Building on the computational privacy theme, Garbled Circuits offer a pragmatic alternative for secure multi-party scenarios, where participants jointly evaluate functions on private inputs without intermediaries. Originating from Andrew Yao's protocol, Garbled Circuits “garble” a Boolean circuit so that evaluators can compute outputs using encrypted keys, revealing only the result while keeping inputs hidden. This technique is ideal for low-latency environments, making it suited to onchain applications requiring fast, private executions.
In web3 gaming, for example, Garbled Circuits can facilitate fair multiplayer outcomes, such as resolving bets or auctions without disclosing bids to prevent collusion. They also empower confidential voting systems, where ballots are processed securely to tally results without revealing individual decisions, which is ideal for DAOs. Benefits associated with Garbled Circuits include lightweight implementation compared to heavier cryptographic schemes, and scalability, achieving sub-second speeds for complex functions.
COTI's Layer 2 network harnesses Garbled Circuits to deliver privacy-preserving transactions, transforming areas like institutional finance by enabling compliant, auditable computations at scale. This efficiency positions Garbled Circuits as a bridge between theoretical privacy and practical deployment, particularly where resource constraints challenge other methods. With ZKPs, FHE, and Garbled Circuits in the bag, there’s just one more encryption technology needed to round out this list – and it’s another acronym.
As cryptographic approaches such as Garbled Circuits advance, hardware-assisted solutions such as Trusted Execution Environments (TEEs) provide a further layer of assurance, leveraging secure enclaves to isolate computations. Exemplified by Intel SGX or ARM TrustZone, TEEs create tamper-proof “black boxes” within processors where code runs in encrypted memory, shielded from the host system – including the blockchain node itself. This hardware-software hybrid ensures that sensitive operations occur in a verifiable, confidential space, with remote attestation proving enclave integrity.
In web3, TEEs support private smart contracts for enterprise use cases, such as cross-chain asset bridges where confidential swaps can occur without exposing proprietary data. They also support decentralized oracles feeding encrypted data to dapps such as real-time market feeds for DeFi without leakage. Key benefits encompass faster performance than pure cryptography and resilience against software attacks, though they require trust in hardware manufacturers.
Networks like Oasis Protocol utilize TEEs for confidential computing, allowing developers to build scalable, privacy-focused applications that integrate seamlessly with public blockchains. By grounding privacy in physical safeguards, TEEs offer a robust counterpoint to software-only innovations. They play a pivotal role in giving developers freedom to create smart contracts that are fully private, partially private, or fully public.
As these technologies mature, they are collectively helping to mainstreaming onchain privacy, transforming web3 from a transparent ledger into a framework where transparency and privacy can be deftly balanced. ZKPs provide verifiable anonymity, FHE enables encrypted analytics, Garbled Circuits deliver efficient multi-party security, and TEEs offer hardware-enforced isolation, each addressing distinct challenges while synergizing when incorporated into hybrid models.
You don’t need to be a budding futurologist to appreciate the benefits engendered by versatile privacy frameworks permeating the onchain landscape. From private DeFi to ethical AI deployments, it’s all out there waiting to be deployed once the ability to mask sensitive data is available to builders and users in one click. The tech to facilitate this has been invented, practical implementations have been developed, and now all that’s left is for blockchain projects to slot it into their respective stacks. Once that’s done, we’ll be able to stop talking about privacy because the battle to reclaim it will have been well and truly won.