In-Depth Research Report on Privacy Coins: From Anonymous Assets to a Paradigm Shift Towards Compliant Privacy Infrastructure

Author: Huobi Growth Academy|

Summary

As institutional funds continue to increase their share in the crypto market, privacy is shifting from a marginalized anonymous demand to a critical infrastructure capability for integrating blockchain into real-world financial systems. Blockchain’s transparency was once considered its core value proposition, but with institutional participation becoming dominant, this feature reveals structural limitations. For enterprises and financial institutions, fully exposing transaction relationships, position structures, and strategic rhythms constitutes significant business risks. Privacy thus is no longer an ideological choice but a necessary condition for blockchain’s large-scale, institutionalized application. Competition in the privacy track is also shifting from “strength of anonymity” to “system compatibility.”

1. The Institutional Ceiling of Fully Anonymous Privacy: Advantages and Challenges of the Monero Model

Represented by Monero, the fully anonymous privacy model constitutes the earliest and most “pure” technical route in the privacy track. Its core goal is not to balance transparency and privacy but to minimize observable on-chain information, cutting off third parties’ ability to extract transaction semantics from public ledgers as much as possible. Around this goal, Monero employs mechanisms such as ring signatures, stealth addresses, and RingCT to mask the sender, receiver, and amount simultaneously: external observers can confirm “a transaction occurred” but cannot definitively reconstruct transaction paths, counterparties, or values. For individual users, this “default, unconditional privacy” experience is highly attractive—it turns privacy from an optional feature into a systemic norm, greatly reducing the risk of “financial behaviors being tracked by data analysis tools long-term,” and providing users with near-cash anonymity and unlinkability in payments, transfers, and asset holdings.

Technically, the value of fully anonymous privacy lies not only in “hiding” but also in its systemic design to counter on-chain analysis. The biggest externality of transparent chains is “composable monitoring”: the publicly available information of a single transaction is pieced together over time through address clustering, behavior pattern recognition, and off-chain data cross-validation, gradually linking to real identities, ultimately forming “financial profiles” that can be priced and abused. Monero’s significance is that it raises the cost of this path to a level sufficient to change behavior—when large-scale, low-cost attribution analysis becomes unreliable, the deterrent effect of monitoring and the feasibility of scams decline in tandem. In other words, Monero is not only serving “bad actors,” but also responding to a fundamental reality: in a digital environment, privacy is part of security itself. However, the fundamental issue with fully anonymous privacy is that its anonymity is irrevocable and unconditional. For financial institutions, transaction information is not only essential for internal risk control and auditing but also a legal obligation under regulatory requirements. Institutions need to retain traceable, explainable, and submit-able evidence chains within frameworks like KYC/AML, sanctions compliance, counterparty risk management, anti-fraud, taxation, and accounting audits. Fully anonymous systems “permanently lock” this information at the protocol level, making compliance structurally impossible—even if they are willing to comply subjectively. When regulators require explanations of fund sources, proof of counterparty identities, or disclosure of transaction amounts and purposes, institutions cannot restore key information from the chain nor provide verifiable disclosures to third parties. This is not a matter of “regulators not understanding technology,” but a direct conflict between institutional goals and technical design—the baseline of modern financial systems is “auditability when necessary,” while the baseline of fully anonymous privacy is “impossible to audit under any circumstances.”

This conflict manifests externally as the systematic rejection of strong anonymous assets by mainstream financial infrastructure: exchanges delist, payment and custody providers do not support them, and compliant funds cannot enter. Notably, this does not mean the demand disappears. Instead, demand often migrates to more covert, higher-friction channels, creating a “regulatory vacuum” and a thriving “gray intermediary” market. In Monero’s case, instant exchange services have at times absorbed large volumes of purchase and conversion demand, with users paying higher spreads and fees for accessibility, and bearing costs such as fund freezing, counterparty risk, and opaque information. More critically, the business models of such intermediaries may introduce ongoing structural selling pressure: when service providers quickly convert Monero fees into stablecoins and cash out, the market experiences passive selling unrelated to genuine buy orders, long-term suppressing price discovery. A paradox thus emerges: the more mainstream channels exclude privacy, the more demand concentrates in high-friction intermediaries; the stronger these intermediaries, the more distorted the price; and the more distorted the price, the harder mainstream funds find it to evaluate and enter via “normal markets,” creating a vicious cycle. This process is not about “markets not recognizing privacy,” but about the combined influence of institutional and channel structures.

Therefore, evaluating the Monero model should not stop at moral debates but return to the practical constraints of institutional compatibility: fully anonymous privacy is “default safe” in personal contexts but “default unavailable” in institutional contexts. The more extreme its advantages, the more rigid its dilemmas become. Even if privacy narratives heat up in the future, the main battlefield for fully anonymous assets will remain among non-institutionalized demands and specific communities; in the institutional era, mainstream finance is more likely to choose “controllable anonymity” and “selective disclosure”—protecting trade secrets and user privacy while providing audit and regulatory evidence under authorized conditions. In other words, Monero is not a technical failure but is locked into use cases that institutions cannot accommodate: it demonstrates that strong anonymity is technically feasible, but also clearly shows that—once finance enters an era of compliance—the focus of privacy competition will shift from “whether everything can be hidden” to “whether everything can be proven when needed.”

2. The Rise of Selective Privacy

Against the backdrop of fully anonymous privacy reaching institutional ceilings, the privacy track is shifting directionally. “Selective privacy” becomes a new compromise path between technology and regulation. Its core is not to oppose transparency but to introduce controllable, authorizable, and disclosable privacy layers on top of a default verifiable ledger. The fundamental logic of this shift is that privacy is no longer seen as an escape tool for regulation but as a foundational infrastructure capability that can be absorbed by institutions. Zcash is a pioneering early practice in the selective privacy path. Its design features both transparent addresses (t-addresses) and shielded addresses (z-addresses), giving users the freedom to choose between openness and privacy. When using shielded addresses, the sender, receiver, and amount are encrypted and stored on-chain; when compliance or audit needs arise, users can disclose full transaction details to specific third parties via “view keys.” This architecture is milestone-level in concept: it explicitly states that privacy does not have to come at the expense of verifiability, and compliance does not necessarily mean complete transparency.

From an institutional evolution perspective, Zcash’s value lies not in its adoption rate but in its “concept validation” significance. It proves that privacy can be optional rather than a default system state, and that cryptographic tools can reserve technical interfaces for regulatory disclosure. This is especially important in the current regulatory context: major jurisdictions worldwide do not deny privacy itself but reject “unverifiable anonymity.” Zcash’s design directly responds to this core concern. However, as selective privacy shifts from “personal transfer tool” to “institutional transaction infrastructure,” structural limitations of Zcash become apparent. Its privacy model remains essentially a binary choice at the transaction level: a transaction is either fully public or fully hidden. For real-world financial scenarios, this binary structure is too coarse. Institutional transactions involve multiple participants and responsibilities—counterparties need to verify performance conditions, clearing and settlement agencies need to know amounts and timing, auditors need to verify complete records, and regulators may only care about fund sources and compliance attributes. These entities’ information needs are asymmetric and not fully overlapping.

In this context, Zcash cannot componentize transaction information or differentiate authorization levels. institutions cannot disclose only “necessary information” but must choose between “full disclosure” and “full concealment.” This means that once complex financial processes are involved, Zcash either exposes too much sensitive business information or fails to meet basic compliance requirements. Its privacy capabilities are thus difficult to embed into real institutional workflows, remaining marginal or experimental. In contrast, Canton Network exemplifies another approach to selective privacy. Canton does not start from “anonymous assets” but from the business processes and institutional constraints of financial institutions. Its core idea is not “hiding transactions” but “managing information access rights.” Using the Daml smart contract language, Canton splits a transaction into multiple logical components, with different participants only able to see data relevant to their permissions; other information is isolated at the protocol layer. This design is fundamentally transformative. Privacy is no longer an after-the-fact attribute of transactions but embedded into contract structures and permission systems, becoming part of the compliance process.

From a macro perspective, the differences between Zcash and Canton reveal divergent directions in the privacy track. The former remains rooted in the crypto-native world, seeking a balance between personal privacy and compliance; the latter actively embraces the real financial system, engineering privacy into workflows and institutional frameworks. As institutional funds’ share in the crypto market continues to grow, the main battlefield of privacy will shift accordingly. Future competition will no longer be about who can hide most thoroughly but about who can be compliant, auditable, and scalable without unnecessary information exposure. Under this standard, selective privacy is no longer just a technical route but a necessary pathway to mainstream finance.

3. Privacy 2.0: Upgrading from Transaction Hiding to Privacy Computing Infrastructure

Once privacy is redefined as a necessary condition for institutional on-chain activity, the technological boundaries and value extensions of the privacy track also expand. Privacy is no longer merely about “whether transactions are visible,” but about whether systems can perform computation, collaboration, and decision-making without exposing data itself. This shift marks the transition from “Privacy Asset / Privacy Transfer” phase 1.0 to a phase 2.0 centered on privacy computing, elevating privacy from optional features to universal infrastructure. In the Privacy 1.0 era, technical focus was mainly on “what to hide” and “how to hide,” such as obscuring transaction paths, amounts, and identity links; in the Privacy 2.0 era, the focus shifts to “what can be done while remaining hidden.” This distinction is crucial. Institutions do not only need privacy-preserving transfers but also require complex operations like transaction matching, risk calculation, clearing and settlement, strategy execution, and data analysis under privacy constraints. If privacy only covers payment layers and cannot extend to business logic layers, its value for institutions remains limited.

Aztec Network exemplifies this shift within blockchain systems. Aztec does not treat privacy as a tool to oppose transparency but embeds it as a programmable property within smart contract execution environments. Using zero-knowledge proof-based Rollup architecture, Aztec allows developers to finely define which states are private and which are public at the contract level, enabling “partial privacy, partial transparency” logic. This capability allows privacy to extend beyond simple transfers to cover lending, trading, vault management, DAO governance, and other complex financial structures. However, Privacy 2.0 does not stop at native blockchain solutions. With the rise of AI, data-intensive finance, and cross-institutional collaboration needs, relying solely on on-chain zero-knowledge proofs becomes insufficient. Consequently, the privacy track is evolving toward a broader “privacy computing network.” Projects like Nillion, Arcium, and others are emerging in this context. Their common feature is that they do not aim to replace blockchain but serve as a privacy collaboration layer between blockchain and real-world applications. Through multi-party secure computation (MPC), fully homomorphic encryption (FHE), and zero-knowledge proofs (ZKP), data can be stored, invoked, and computed in encrypted form throughout the process, with participants able to perform model inference, risk assessment, or strategy execution without accessing raw data. This capability elevates privacy from “transaction layer property” to “computing layer capability,” expanding potential markets into AI inference, dark pools, RWA data disclosure, and enterprise data collaboration.

Compared to traditional privacy coins, the value logic of privacy computing projects has shifted significantly. They no longer rely on “privacy premiums” as core narratives but depend on functional indispensability. When certain computations cannot be performed openly or doing so would cause serious business risks and security issues, privacy computing becomes a “must-have” rather than a “nice-to-have.” This also grants the privacy track a potential “bottom moat”: once data, models, and workflows are entrenched within a privacy computing network, migration costs will be substantially higher than ordinary DeFi protocols. Another notable feature of Privacy 2.0 is engineering, modularization, and invisibility. Privacy is no longer explicitly embodied as “privacy coins” or “privacy protocols,” but decomposed into reusable modules embedded into wallets, account abstractions, Layer2 solutions, cross-chain bridges, and enterprise systems. End users may not even realize they are “using privacy,” but their asset balances, trading strategies, identity links, and behavioral patterns are protected by default. This “invisible privacy” aligns more closely with practical large-scale adoption paths.

Meanwhile, regulatory focus shifts accordingly. In Privacy 1.0, the core regulatory question was “does it have anonymity”; in Privacy 2.0, it becomes “can it verify compliance without exposing raw data.” Zero-knowledge proofs, verifiable computation, and rule-based compliance thus become key interfaces for dialogue between privacy projects and regulatory regimes. Privacy is no longer viewed as a risk source but as a technical means to achieve compliance. Overall, Privacy 2.0 is not a simple upgrade of privacy coins but a systemic response to “how blockchain integrates into the real economy.” It signifies a shift in the competitive dimensions of the privacy track—from asset layer to execution layer, from payment layer to computation layer, from ideology to engineering capability. In the institutional era, truly valuable privacy projects may not be the most “mysterious,” but the most “usable.” Privacy computing embodies this logic at the technical level.

4. Conclusion

In summary, the core dividing line in the privacy track is no longer “whether privacy exists,” but “how to use privacy under compliance.” Fully anonymous models offer irreplaceable security value at the personal level, but their unregulatable nature makes them unsuitable for institutional-level financial activities; selective privacy, with its design of disclosability and authorizability, provides a feasible technical interface between privacy and regulation; and the rise of Privacy 2.0 further upgrades privacy from an asset property to a foundational infrastructure for computation and collaboration. In the future, privacy will no longer exist as an explicit function but will be embedded as a default assumption in various financial and data workflows. Truly valuable privacy projects may not be the most “secret,” but they will be the most “usable, verifiable, and compliant.” This marks a key milestone in the transition of the privacy track from experimental to mature stage.