History of Privacy Development in the Cryptocurrency Field
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History of Privacy Development in the Cryptocurrency Field
Privacy technologies in the crypto world have never truly stepped out of the "narrow" and "single-user" paradigm.
Navigating Web3 tides with focused insightsAuthor: milian
Translation: AididiaoJP, Foresight News
Every major technological wave begins with specialized or single-user systems before evolving into general-purpose, multi-user platforms.
Early computers performed one task at a time: breaking codes, processing censuses, calculating ballistic trajectories—only much later did they become shared, programmable machines.
The internet began as a small peer-to-peer research network (ARPANET), eventually growing into a global platform enabling millions to collaborate in a shared environment.
Artificial intelligence follows the same trajectory: early systems were narrow expert models built for specific domains (chess engines, recommendation systems, spam filters), later evolving into general models capable of cross-domain tasks, fine-tuning for new purposes, and serving as shared foundations for others to build upon.
Technology always starts narrow or single-user, designed for one use or one person, before expanding into multi-user modes.
This is precisely where privacy technology stands today. Privacy tech in crypto has never truly escaped the confines of "narrow" and "single-user" designs.
Until now.
Summary:
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Privacy technology follows the same evolution as computing, internet, and AI: from specialized, single-user systems to general-purpose, multi-user platforms.
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Crypto privacy has long been stuck in narrow single-user mode because early tools couldn't support shared state.
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Privacy 1.0 is limited single-user privacy: no shared state, primarily relying on zero-knowledge proofs, client-side proof generation, custom circuit development by engineers, resulting in poor developer experience.
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Early privacy began with Bitcoin's CoinJoin in 2013, followed by Monero in 2014, Zcash in 2016, and later Ethereum tools like Tornado Cash (2019) and Railgun (2021).
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Most Privacy 1.0 tools rely on client-side zero-knowledge proofs, leading to confusion between "zero-knowledge for privacy" and "zero-knowledge for verification," even though many modern "zero-knowledge" systems are designed for verification, not privacy.
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Privacy 2.0 enables multi-user encrypted shared state via secure multi-party computation (MPC) or fully homomorphic encryption (FHE), allowing private collaboration analogous to how users cooperate over public shared states on Ethereum and Solana.
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Encrypted shared state means crypto finally has a general-purpose encrypted computer, unlocking entirely new design spaces: dark pools, private pools, confidential lending, blind auctions, secret tokens, novel creative markets—and these can run atop existing transparent chains.
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Bitcoin introduced public isolated state; Ethereum brought public shared state; Zcash delivered encrypted isolated state; Privacy 2.0 completes the puzzle: encrypted shared state.
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Arcium is building such an encrypted computer, architecturally similar to proof networks like Succinct, but replacing zero-knowledge proofs with MPC. Its Arcis tool compiles Rust into MPC programs, enabling multi-user encrypted computation.
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Emerging applications based on Privacy 2.0 include: Umbra using Arcium for confidential balance and exchange privacy pools, Pythia’s private opportunity market, Melee’s upcoming opinion markets with private odds and adjudication.
To understand how we arrived here, and why encrypted shared state matters so much, we must begin at the origins of privacy technology.
Privacy 1.0
The first storm of crypto privacy emerged here.
Users gained transaction privacy through mixers, privacy pools, and privacy-focused cryptocurrencies. Later, some applications faced legal challenges, sparking debates about whether and how privacy tools should handle illicit activities.
Privacy 1.0 established the single-user privacy paradigm. People could coordinate, but not dynamically collaborate as they do on programmable blockchains. Expressiveness remained constrained.
Key characteristics of Privacy 1.0:
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No shared state—privacy operates in “single-user mode,” limiting application scope
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Primarily relies on zero-knowledge proof technology
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Client-side zero-knowledge proofs offer maximum privacy but suffer slow performance for complex applications
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Poor developer experience requiring custom circuit writing to build privacy apps
Crypto privacy actually originated on Bitcoin years before advanced cryptography like zero-knowledge proofs entered the space. Early Bitcoin privacy wasn’t true “cryptographic privacy,” but clever coordination techniques aimed at breaking deterministic linkages on public ledgers.
The earliest was CoinJoin in 2013, where users merged transaction inputs and outputs to obscure payment relationships. It used almost no cryptography but introduced transaction-level privacy.
Later came applications like CoinShuffle (2014), JoinMarket (2015), TumbleBit (2016), Wasabi (2018), Whirlpool (2018), all based on mixing processes to make Bitcoin harder to trace. Some added incentives, layered encryption, or improved UX.
These did not provide strong cryptographic privacy. They obscured linkability but lacked the mathematical guarantees and trustless privacy offered by later zero-knowledge proof systems. They relied on coordination, heuristics, and mixing randomness rather than formal anonymity proofs.
Privacy Cryptocurrencies
Monero launched in 2014 as the first serious attempt to build a fully private blockchain for confidential transfers—not just a privacy add-on for transparent blockchains. Its model uses probabilistic privacy via ring signatures, mixing each real input among 16 decoy signatures by default. In practice, this setup may be weakened by statistical attacks like MAP decoders or network-layer attacks, reducing effective anonymity. Future upgrades like FCMP aim to expand the anonymity set to the entire chain.
Zcash launched in 2016, taking a radically different path from Monero. Instead of probabilistic privacy, it was designed from the start as a zero-knowledge proof-native token. It introduced a zk-SNARKs-powered privacy pool, offering users cryptographic privacy instead of hiding behind decoy signatures. When used correctly, Zcash transactions reveal neither sender, receiver, nor amount, and anonymity increases with every additional transaction in the pool.
The Emergence of Programmable Privacy on Ethereum
Tornado Cash (2019)
Tornado Cash launched in 2019, bringing programmable privacy to Ethereum for the first time. Though limited to private transfers, users could now deposit assets into a smart contract mixer and withdraw later using zero-knowledge proofs, achieving real privacy on a transparent ledger. Tornado was widely used legally, but became embroiled in severe legal disputes after extensive DPRK money laundering flowed through it. This highlighted the necessity of excluding bad actors to maintain pool integrity—a measure now adopted by most modern privacy applications.
Railgun (2021)
Railgun appeared later in 2021, aiming to push Ethereum privacy beyond simple mixing toward private DeFi interactions. It not only mixes deposits and withdrawals but also allows users to privately interact with smart contracts using zero-knowledge proofs, hiding balances, transfers, and on-chain operations while still settling on Ethereum. This represented a major leap beyond the Tornado model, providing persistent private state within smart contracts rather than just a mix-and-withdraw cycle. Railgun remains active and has seen adoption in certain DeFi circles. It remains one of the most ambitious attempts at programmable privacy on Ethereum, though user experience remains a key barrier.
Before proceeding, a widespread misconception must be clarified. As zero-knowledge proof systems gained popularity, many assumed that anything labeled "zero-knowledge" implies privacy. This is incorrect. Most technologies marketed as "zero-knowledge" today are actually validity proofs—excellent for scalability and verification, but offering no privacy at all.
This marketing-reality gap caused years of misunderstanding, conflating "zero-knowledge for privacy" with "zero-knowledge for verification," despite solving entirely different problems.
Privacy 2.0
Privacy 2.0 is multi-user mode privacy. Users no longer act alone but can collaborate privately, just as they do on programmable blockchains.
Key features of Privacy 2.0:
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Encrypted shared state—privacy enters “multi-user mode”
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Built on secure multi-party computation (MPC) and fully homomorphic encryption (FHE)
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Trust assumptions depend on MPC. FHE shares the same assumption since threshold decryption of encrypted shared state requires MPC execution
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Circuits are abstracted away—developers don’t need to write custom circuits (unless desired)
This is enabled by encrypted computers allowing multiple parties to collaboratively compute over encrypted state. MPC and FHE are the foundational technologies—both support computation on encrypted data.
What does this mean?
The shared state model powering Ethereum and Solana can now exist under privacy-preserving conditions. This isn’t just about single private transactions or tools that merely prove something privately—it’s a general-purpose encrypted computer.
It unlocks an entirely new design space in crypto. To understand why, consider the evolution of state in crypto:
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Bitcoin introduced public isolated state
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Ethereum introduced public shared state
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Zcash introduced encrypted isolated state
What’s been missing is encrypted shared state.
Privacy 2.0 fills this gap. It spawns new economies, new applications, and unprecedented domains. In my view, this is the most significant breakthrough in crypto since smart contracts and oracles.
Arcium is building exactly this kind of technology.
Its architecture resembles proof networks like Succinct or Boundless, but instead of using zero-knowledge proofs for validation, it uses MPC for encrypted data computation.
Unlike SP1 or RISC Zero compiling Rust into zero-knowledge proof programs, Arcium’s Arcis compiles Rust into MPC programs. Simply put: it’s an encrypted computer.
Another analogy: the “Chainlink of privacy.”
Blockchain- and Asset-Agnostic Privacy
Arcium is blockchain-agnostic by design, connectable to any existing blockchain, enabling encrypted shared state on transparent chains like Ethereum and Solana. Users gain privacy without leaving their familiar ecosystems. It will launch first on Solana, with its mainnet Alpha releasing this month.
Zcash and Monero embed privacy directly into their native currencies. This works well but creates separate monetary worlds with independent volatility. Arcium takes an asset-agnostic approach, adding privacy to users’ existing assets. The trade-offs differ, but flexibility is crucial for users.
Given this, nearly any use case requiring privacy can now run on encrypted computation.
Arcium’s impact extends beyond crypto. It’s not a blockchain—it’s an encrypted computer. The same engine clearly applies to traditional industries as well.
Zero-to-One Applications and Capabilities
Encrypted shared state opens unprecedented design possibilities in crypto. Thus, the following applications emerge:
@UmbraPrivacy: Solana privacy pool. Umbra uses Arcium to deliver functionality Railgun cannot—supporting confidential balances and private swaps, while using zero-knowledge proofs for transfers. It offers far more than simple private transfers under minimal trust assumptions, and provides a unified privacy pool SDK that any project can integrate for Solana transaction privacy.
@PythiaMarkets: Opportunity markets with private windows for sponsors. A new type of information market where scouts bet on underexplored opportunities, and sponsors discover alpha without revealing it.
@MeleeMarkets: Prediction markets with bonding curves. Similar to Pumpfun, but for prediction markets—earlier entry gets better pricing. Will develop opinion markets where users express genuine views, odds remain private, and adjudication occurs privately, solving issues of groupthink and oracle manipulation. Arcium will provide the necessary privacy for opinion markets and private adjudication.
Dark Pools: Projects like @EllisiumLabs, @deepmatch_enc, and Arcium’s dark pool demo use encrypted shared state for private trading, avoiding front-running and order book scraping to achieve optimal execution prices.
On-chain Gaming: Arcium restores secrecy and fair randomness by running hidden states and CSPRNG-based random number generation within encrypted shared state. Strategy games, card games, fog-of-war mechanics, RPGs, and bluffing games can finally operate on-chain. Multiple games are already live on Arcium.
Private perpetuals, private lending, blind auctions, encrypted machine learning predictions, and collaborative AI training are also exciting future use cases.
Beyond these examples, nearly any product needing privacy can be built. Arcium gives developers full customization through a universal encrypted execution engine. Umbra now also offers an SDK for Solana transfers and swaps. Together, they make implementing privacy on Solana straightforward—for both complex systems and simple integrations.
C-SPL: A New Confidential Token Standard for Solana
Arcium is also building C-SPL, the Confidential SPL standard for Solana. It addresses pain points of previous Solana “Privacy 1.0” token standards: difficult integration, limited functionality, and incompatibility with on-chain programs. C-SPL improves upon these, removing friction that hindered widespread adoption of privacy tokens.
This makes privacy tokens easy to integrate into any application without burdening users.
By integrating SPL Token, Token-2022, privacy transfer extensions, and Arcium’s encrypted computation, C-SPL delivers a practical, fully composable standard for confidential tokens on Solana.
Conclusion
We’re still in the early stages of this wave, and the field is broader than any single approach. Zcash and Monero continue solving important problems in their domains, and early privacy tools have demonstrated what’s possible. Encrypted shared state addresses a completely different dimension—enabling multiple users to operate privately over shared state without leaving existing ecosystems. It fills a gap, not replaces the past.
Privacy is gradually shifting from an optional niche feature to a core building block for applications. It no longer requires new currencies, new chains, or new economic systems—it simply expands the developer toolkit. The last era established public shared state as foundational. The next era will extend that foundation through encrypted shared state, adding a layer that was previously missing.
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