平凡的蛙里奥

Can a privacy chain be positioned like this?

It says @Dusk can serve as a privacy-preserving sidechain for any L1

The whitepaper is very direct: Dusk was never designed to be a one-size-fits-all public chain. It’s targeting “regulated security tokenization and end-to-end lifecycle management.”

Two standards are what prop up the show.

One is XSC. The privacy-preserving security contract standard’s whitepaper even writes very modestly that the details are outside the scope of this paper. If you want to learn more, look for another document [Mah21].

I was stunned at the time—this was the first whitepaper I’d seen that effectively handed over its most important application-layer standard to external references, and then I traced through it. This set of standards covers the whole sequence for tokenized securities: from issuance, to voting, to dividends.

The other is the privacy token standard. This one is even more clever: it allows regulated and unregulated assets to interact on the same chain without sacrificing participants’ privacy. My understanding is that this is the privacy bridge built between DUSK (which operates with unregulated assets) and security tokens.

They don’t need to know each other on either side to safely work together.

As long as you pair it with a trustworthy or trust-minimized interoperability solution, projects on other L1s don’t need to migrate their chains. They can simply use Dusk as a privacy execution layer. This idea is something I haven’t seen in other privacy-chain documents: privacy is no longer a single-chain island—it becomes a capability that others can borrow.

Put simply: if another chain’s assets want to keep things private, they don’t need to move home. Just drive the asset to Dusk’s privacy workshop, process it there, and drive it back. I think this positioning is much lighter than “issuing another privacy chain.”

One more small detail: in the architecture, the protocol is split into two non-overlapping layers—an native asset layer and a general computation layer. They share the same state space, but DUSK retains several exclusive privileges: only it can be used for staking; only it can pay execution fees; and DUSK contracts are the only entry point into state transitions. The boundary between the asset layer and computation layer is drawn very clearly. It means that no matter how big the on-chain ecosystem grows, the demand to “consume DUSK” can’t be avoided.

Of course, all of this narrative only holds if the upper-layer standards are actually being used. If XSC never takes off, or if security-tokenization projects don’t arrive for a long time, then “a privacy sidechain” is just a pretty empty promise.

My suggestion: first check whether real security token contracts show up on the testnet, and then consider whether to get on the train. #dusk $DUSK

In our little circle, everyone thinks they’re a trading genius.

Do you know someone like—where everyone says he’s a genius, but he ends up being so oppressive that other traders can’t hold their heads up?

Please recommend one to me—I want to go learn from him.

I've been thinking about how to play @TermMax lately, and I find its design of splitting debt into FT and XT pretty interesting. The lender buys FT to lock in fixed returns, while the borrower tosses out XT to swap for liquidity—effectively slicing and pricing interest-rate risk directly. That’s much clearer than the usual game-theory mixing in traditional lending pools.

That said, for this mechanism to work, it really depends on the Range Order AMM’s market-making logic. It uses a target APR range instead of a price range, and the curve can automatically recalculate based on the maturity date. It sounds more aligned with how interest-rate markets behave than V3, but whether the slippage and depth can withstand extreme conditions is something I still need to observe.

I also think the GT NFT leverage wrapper is a highlight. With a single transaction, you can move directly to a target leverage level, saving gas from repeated loop collateralization and reducing liquidation risk. But on the flip side, leverage amplifies both gains and losses. Combined with oracle dependency, if on-chain data sources malfunction, the chain reaction could be even more severe than in traditional lending.

The curator mechanism actually makes me feel a bit more comfortable. Professional teams like Keyrock manage liquidity, and idle funds can be automatically deployed into Aave or Morpho to earn yield—so capital isn’t just sitting idle. However, this also means the protocol becomes more reliant on third parties; if a curator strategy misfires, the impact could directly propagate to users.

From the data: TVL is 64 million, peak daily active users reach 170,000, and it’s deployed across 7 chains—showing the ecosystem is indeed expanding. But I think the real test after the TGE is whether it can retain TVL. TMX’s total supply is 1 billion and won’t be increased. Ecosystem tokens are locked for 48 months; the team and investors’ allocations are linearly released after 12 months. The overall pace is fairly restrained. The protocol stakes sTMX to earn trading fees, borrowing fees, and liquidation fees—its revenue sources feel fairly solid rather than purely propped up by inflation.

However, if after the token listing in 2026 Q3 the TVL doesn’t keep up, or if bad-debt controls don’t work out, then my assessment may have to be overturned.

In practice, I think it’s best not to rush. First, watch the rollout of the Q2 options expansion and the strategy vaults. Pay special attention to how GT performs liquidation under extreme volatility, and to the real returns of curators’ deployed capital. If those two hold up, then consider building positions in batches. After all, the interest-rate sector has low tolerance for mistakes—leaving room for error matters more than just reciting slogans.
#termmax

This is the highest-traffic post I’ve had since Binance

I really didn’t expect
that my first time would go to a cow

Speaking of cows—in my view, the most powerful privacy project I have is @Dusk
not the kind of self-hype where “I used some consensus so I’m so great”

It’s that it actually did something that everyone thought was impossible.

Privacy and compliance—these two are supposed to be sworn enemies. The deeper you hide, the more nervous regulators get. But Dusk took a third path.

The most mind-boggling design is called Proof-of-Blind Bid.
On other chains, everyone can see who produces blocks and how much is staked—basically laying the validator’s cards on the table. Dusk doesn’t play that game.

The staking amount is wrapped with Pedersen commitments, and then a zero-knowledge proof is used to tell the network, “I’m eligible to produce blocks,”
but it doesn’t reveal who you are or how much you staked.

A group of people wear masks and vote in the dark in a dim room.
If an attacker wants to cause trouble?

They can’t even find the target.

For the trading side, Phoenix handles anonymity. Each transaction generates a one-time address. The anonymous set is the total of all cumulative outputs from the genesis block to now— the more people use it, the deeper your privacy. Not something propped up by a mixing pool.

Another one: Zedger
Specially designed for security tokenization—regulatory requirements like whitelists, recipient approval, and equity snapshots are written one by one into the protocol layer, not the contract layer, into the protocol itself.

The chain itself was built like this.
While others are still debating how to put assets on-chain,
Dusk is already answering how to meet regulatory requirements after assets are on-chain.

The technical foundation is solid too.

Rusk VM is built on the WASM architecture, with native support for on-chain ZK verification.
The cryptography components hash uses both Blake2b and Poseidon. Signatures use both Schnorr and BLS.
Most whitepapers stop at this level with a line like “uses industry-standard mainstream solutions,” but Dusk specifies every screw’s exact model.

Tokenomics are not exaggerated either.
Total supply capped at 1 billion. Halves every four years. Any block rewards that aren’t distributed are directly burned. The more active the network, the more it burns: #dusk $DUSK

Recently, there’s some outrageous chatter going around in the local circles—rumors that say TermMax’s range-order lending/borrowing model “stole” the method used by Xu Qihang (Evergrande’s) back then.

However, when I open the @TermMax whitepaper and break down its on-chain logic, I find that this is just too...
It didn’t borrow from Evergrande at all. Instead, it uses code to build a mechanism that is completely the opposite of Evergrande.

#termmax splits every dollar into two tokens: FT (the principal coin) represents the principal that is rigidly settled at maturity, while XT (the interest coin) represents floating interest yield.

Your principal safety doesn’t depend on any platform’s promises. It’s protected by real assets locked in smart contracts. There’s no Ponzi-style structure of “borrowing new to repay old.”

Interest rates can be “targeted at specific points” by borrowing Uniswap V3’s concentrated liquidity mechanism. TermMax lets you define your own rate range for limit orders.

If you think 8%–10% is reasonable, you only place orders within that range. If the rate goes off target, your order won’t get filled—avoiding the passive “all-or-nothing” situation typical of traditional lending pools.

It also supports multi-range orders. For example, 80% of the funds are placed for stable rates, and 20% is used to chase higher interest—flexible like placing batches of limit orders.

The fundamental difference from Evergrande:
Evergrande manufactures “guaranteed returns” through paper guarantees and capital-pool shuffling, with unclear accounting—leading to the eventual blow-up.

With TermMax, all orders, interest rates, and reserve quantities are fully verifiable on-chain. Interest rates are market-matched based on supply and demand within a predefined range. Risk control is handled by automatic execution through smart contracts.

In one sentence: Evergrande is run by people. TermMax is “run by code.”

So why is there a rumor that confuses DeFi fixed-rate lending with Evergrande wealth management?

Because both of them promise “guaranteed returns.”
But the essential difference is: Evergrande’s “guarantee” relies on paper guarantees and capital-pool maneuvering, whereas TermMax’s “guarantee” comes from the smart contract’s atomic splitting of principal and interest plus real-time on-chain settlement.

The former is trust in people; the latter is trust in mathematics. They have a fundamental difference.

Former Japanese AV actress retired and turned to programming, using Claude Code to write code

A girl who used to shoot AV hard-coded her way through with AI programming tools

I used to think writing code was a huge hurdle, but now the barrier has been flattened
No more talk—I’m going to revisit it as a keepsake
Chances are, the next time I see her will be as a bald-headed beauty programmer

Actually, this whole thing suddenly sparked a thought in my head
Isn’t project @Dusk also doing something similar? Building a privacy blockchain, setting up a bunch of compliance tools—didn’t they also want to let traditional financial institutions get onto the chain with a low barrier, and do RWA

In the past, these people looked at blockchain the way you’d look at a textbook in the sky, but now #dusk has basically laid the path right at your feet

The design of token $DUSK is also pretty interesting—staking, block production, and compliance, all in one coordinated combo move. Isn’t that basically telling traditional institutions: you don’t have to shed layers of skin to get in

Tech really is something—it's not picky about your background, it doesn’t care what you did before. As long as you’re willing to learn, it will give you a chance

Of course, the biggest surprise for me is the Zedger model. What used to scare people about privacy chains?

Dusk puts the whitelist and equity records directly into the protocol layer. If regulators want to check, they can see. But ordinary people still can’t see other people’s wallets

That’s a pretty slick move—protects privacy, and also prevents compliance folks from picking holes

Phoenix’s UTxO anonymous transaction setup is also quite interesting. As the anonymous set grows with transaction volume, the more people there are, the safer it is

A picture popped into my mind: a group of people wearing masks dance in a square. Nobody knows who anyone is, but the DJ holds a sign-in sheet and knows who bought an entry ticket

Rusk VM natively supports ZK verification, with four genesis contracts
I can’t quite remember the cryptography terms like Poseidon hashes and BLS signatures, but I do know they’re there to make it so the chain only cares about whether things are right or wrong—not about the details

I actually don’t fully understand every detail, but Dusk’s approach really makes me feel that privacy and compliance might not have to be a life-or-death fight

It’s just that I don’t know whether the market will buy into it. After all, everyone’s used to thinking in black and white

My recently divorced lesbian classmate

Always asks me to go out and have fun

I really want to go too, but I can’t
What a pity—I can’t

Lately, I’ve been really annoyed by my floating interest rate

So the first time I saw @TermMax saying it does fixed-rate lending

I read its whitepaper twice
The idea is to split each debt into two tokens, FT and XT, where 1 FT plus 1 XT equals 1 debt token. FT is the principal—it's the zero-coupon bond kind of play. You buy it at a discount; at maturity you redeem it at face value. The moment you buy, the interest rate is locked in. XT is the interest portion. The borrower receives it, and to get liquidity back, they can sell it anytime

If you want certainty, take FT. If you want flexibility, play XT. One debt split into two different personalities

Sounds not complicated, right?

The real work is in pricing. It takes cues from Uniswap V3’s concentrated liquidity, but changes one thing: when market makers place orders, they’re not defining a price range—they’re defining an APR range. I stared at the math in the whitepaper for a long time. The core is that the exchange rate between FT and XT follows a piecewise curve; where it lands in which interest-rate band determines the trade that happens

There’s another detail I think is pretty meticulous: the closer it is to maturity, under the same APR, the FT price should go up and the XT price should go down. So the curve isn’t something you just draw and leave there—it gets recalculated after every executed trade based on the current remaining time

In the market-making lineup there are Keyrock, Edge Capital, Origami Crypto, and others. The whitepaper also specifically describes two strategies to prevent idle funds: any money not lent out automatically gets put into floating protocols like Aave, Morpho, and Venus to earn interest like a savings account

I also skimmed the roadmap. Later there are options, derivatives, and interest-rate swaps. And there’s a GT, which is a leveraged position in the form of an NFT: add the leverage in one transaction, without having to repeatedly post collateral and borrow like in traditional setups. Current TVL is a bit over $60 million, over 800,000 registered wallets, and the peak number of daily active users hit 170,000. The scale isn’t huge, but the mechanism is complete

What I really want to say isn’t actually the technology

"Certainty" is becoming a luxury in the crypto industry

Market conditions are uncertain, policies are uncertain, and sometimes you don’t even know whether this protocol will still be around tomorrow

Everyone is chasing 20%, 30% annualized returns, their eyes shining

But if you think about it carefully, how many people actually want is just this: "put a sum of money in, and at maturity get an amount I already know in advance." That’s it—those are the only requirements

#termmax

Please follow me to turn to Chapter 6 of the white paper

The title is very plain: Cryptographic Primitives. This chapter is the real foundation of privacy—@Dusk

What we discussed earlier about consensus and the transaction model are, in fact, houses built on top of this foundation

I can see a very clear pattern: almost every component is in a "dual-track configuration"

Hashing uses Blake2b for general computation, plus a Poseidon implementation specifically to support zero-knowledge proofs; signatures use Schnorr for everyday needs, then add BLS for aggregate signatures; even the elliptic curves are split into two—JubJub handles ordinary operations, while BLS12-381 is responsible for pairings

My take is that this isn’t just piling on features. It’s because the requirements for hashing in ZK-friendly scenarios are completely different from those in typical settings. Forcing one approach to serve both ends up being uncomfortable, so they simply prepare two separate sets

What struck me most is stealth addresses: they don’t give you a single fixed address to use forever. Instead, based on a Diffie-Hellman key exchange, each transaction generates a fresh one-time public key on the spot

The recipient only reveals the public spend key. The sender uses a random number r to compute the one-time public key and sends the funds. The recipient then scans the transaction again using their view key to recognize, "This one is for me." And if they want to spend it, they must use the secret spend key

See, receive, and spend—three keys each handle their own part. I think this is far more sophisticated than something like "one address used until the end of time." On-chain, nobody can string your multiple incoming payments into a single line

The commitment scheme uses Pedersen: c = v·G + b·H, where G and H are two generators with unknown relationships. It can hide the amount, and it also prevents later cheating by changing it to a different number

Encryption is tool-specific as well: ElGamal is for asymmetric encryption, while Poseidon-SpongeWrap is for symmetric encryption

Even the Merkle tree doesn’t cut corners: the general structure uses Blake2b to compute hashes, and any structure that needs to be fed into a ZK proof is switched to Poseidon. The same idea is carried through to the end

Honestly, seeing this level of meticulous division of labor surprised me a bit

Most white papers stop at this level with a line like "we adopt industry-standard solutions"—just glossing over it, #dusk $DUSK @Dusk

Write seriously, you don’t read it

Send $牛来 and you chase me for
Number plates

That’s what you look like

What I see isn’t a bunch of genius traders

It’s all a bunch of old perverts

Seeing you like this

Reminds me of @TermMax

Many people understand TermMax as a fixed-rate lending platform, but in the whitepaper the GT is a type of NFT-form leveraged token. It encapsulates the entire leveraged position on-chain—what you’ve collateralized and what you owe are all recorded inside this one NFT.

In traditional setups, doing leverage requires repeating the “collateralize → borrow → collateralize again” cycle. Every step burns gas, liquidation lines are scattered everywhere, but here one transaction mints a GT and you reach the target leverage. My take is that this design turns the “leveraged position” itself into a composable asset. Later, if strategy vaults or institutional products want to bundle positions, GT would be ready-made building blocks.

Another piece is XT’s second identity in the Alpha market

Like the existence of an options premium. That means this yield token, besides pairing with loans, can also be played as an options-like instrument. Looking at the roadmap, Q2 has allocations for options and derivatives expansion, strategy product vaults, and money-market integration. After Q4, there are also interest rate swaps. What TermMax wants to build may not be just a lending protocol, but rather an infrastructure for interest-rate derivatives. Current peak daily active users are over 170,000.

I also looked carefully at the allocation structure: community 15%, ecosystem 29%, investors 28%, team 15%, with liquidity provision and the foundation at 5% each, and advisors at 3%.

I’m more concerned about the ecosystem side. At nearly 30%, it’s the largest single share among all categories. The release schedule of that ecosystem share basically determines the pace and ammunition for later ecosystem expansion.

It uses LayerZero’s OFT standard for cross-chain. Later, the cost to connect more EVM chains won’t be high.

For security, it has undergone an ABDK audit and the report is public. In addition, the legal opinion explicitly states that TMX does not constitute a security in major jurisdictions. The compliance stance looks fairly solid.

But there are things to watch out for too:

GT is fundamentally a leveraged position. Leveraging amplifies both gains and losses. Liquidation also depends on a dual oracle system. In extreme market conditions, if the oracle data is off, pricing and liquidation will both go wrong. My advice is: don’t just listen to the narrative—first track the real minting volume of GT positions and the liquidation records.

#termmax

You all said $牛来 is a bad movie. I just specifically watched it a moment ago too, and it’s not too bad—the plot is pretty rich.

#dusk $DUSK @Dusk Previously we discussed the technical side of privacy chains; this time let’s look at something more practical: tokenomics. @Dusk The supply model—after going through the official documentation—it really deserves to be broken down in detail.

Total supply: 500 million initial issuance, plus another 500 million issuance over the following 36 years via staking rewards, with a hard cap at 1 billion tokens. The inflation curve follows geometric decay with r=0.5: every four years, the issuance is halved. In just the first four years, it releases about 250 million tokens—roughly half of the total incremental supply. After that, each period cuts the amount by half again; after more than thirty years, only a bit under 1 million tokens are issued in a single period.

My take is that almost all dilution pressure is concentrated in the first four years. After that, if network demand still hasn’t picked up, it would be hard to keep justifying the later issuance.

More interestingly, 70% of the block reward per block goes to the block producer, and then—up to an additional 10%—is distributed according to the credits in the certificates. Any unallocated portion is directly burned. The remaining 10% goes to the development fund; the validation committee and the approval committee each receive 5%. I think the key detail here is “the remainder is burned.”

Transaction fees are merged into block rewards and then redistributed. The more active the network is, the more fees the block producer earns. Meanwhile, the burn mechanism creates a supply contraction tied to the same variable as usage and deflation.

The penalty mechanism is structured as: light penalties for failed participation—nodes are paused and some active staking is converted into locked staking. Heavy penalties target provable malicious behavior like double-signing: staked deposits can be directly burned, and the reporter of the violation can share in the slashed (penalized) stake.

Making “snitching” a paid activity—this incentive design, in my view, is far more practical than simply stacking up penalty amounts.

The distribution breakdown is also fairly clean: Token Sale is 50%, while the team plus advisors total only 12.8%. Development is 18.1%. All vesting periods are completed by April 2022, so there’s no looming overhang of long-term unlock-and-sell pressure in the market. The minimum staking threshold is 1,000 tokens—$DUSK retail users can also participate in validation.

DuskEVM testnet launched on August 10. Solidity and Hardhat are directly usable, and the mainnet is expected to go live later this year. In the same timeframe, the community is voting on whether to set up an OpenDusk treasury, whose funding source is precisely the block rewards that get burned as mentioned earlier. At the end of July, Santiment ranked dusk in the top ten for RWA development activity. The mainnet only launched in January; the current price is around $0.07, and the market cap is still on the order of tens of millions of dollars.

If the DuskEVM mainnet is delayed again, or after launch there still aren’t real applications for a long time, then even the best economic model is ultimately just paper theory.

I read the whitepaper for @TermMax a few times just now—one covers the Range Order pricing mechanism, and the other is the TMX token whitepaper.

After finishing, I got a pretty strong feeling: this might be the most complete mechanism-design in the DeFi fixed-rate arena.

Let me start with what I find most interesting.
TermMax breaks each debt into two tokens: FT represents principal, and XT represents interest.
1 FT plus 1 XT equals 1 debt token. The lender buys FT at a discount; when it matures, they redeem at face value—so the interest rate is locked in the moment you enter. The borrower receives XT, sells it directly for liquidity—the borrowing cost is locked in as well.

What really made me look twice is its Range Order AMM. Drawing on the concentrated liquidity concept from Uniswap V3, the market maker doesn’t set a price range, but instead sets a target APR range. Using multiple “checkpoints,” it turns the FT↔XT exchange rate into a segmented curve. As the maturity date approaches, the curve is recalculated proportionally by time.

The tricky thing about fixed-income—how the interest rate decays over time—is written directly into the AMM mathematics, rather than being handled manually.

Go one layer deeper: whether it can actually “turn into liquidity” depends on the curator.
Right now, Keyrock and Hardcoded Lab manage the market. Together with atomic orders, liquidity is spread across multiple orders. Any borrowed funds that don’t get lent out automatically get deployed into Aave and Morpho to keep earning. In theory, the system doesn’t have idle capital stuck at zero yield.

My take is that this is exactly how market-maker pricing capability gets productized.

On the data side, TVL has reached over $64 million, with 830,000 registered wallets, and more than 20 institutional partners. It has been deployed on seven chains including Ethereum, BNB Chain, and Arbitrum.

$TMX total supply is 1 billion tokens with no fixed increase. Initial circulating supply is about 20% at TGE. After the 12-month lock-up for the team and investors, linear vesting kicks in over 24 to 30 months. The ecosystem portion vests over 48 months; staking yields sTMX, allowing holders to share “treasury” returns made up of trading fees, borrowing protocol fees, and liquidation fees—linking token value to the protocol’s real revenue.

But having said all that: if after TGE TVL can’t keep up, or bad debt exceeds what the curator can control, or if this mechanism is copied verbatim by big platforms—then even a very clever design is just a paper advantage.

My suggestion: if you want to participate, start with small capital and fully run through the FT and XT mechanics, figure out the lock-price logic, then consider the token layer. Slowing the pace a bit won’t hurt—#TermMax

Many people have a stereotype about privacy chains: privacy equals anti-regulation, and once regulators lock onto a project, it disappears
But the @Dusk whitepaper’s most unexpected part is exactly this
It doesn’t avoid regulation at all—it treats regulatory requirements as design constraints and builds them into the transaction model. It spells out seven clauses in black and white

In the Zedger section of the whitepaper: each user can have only one account; only whitelisted users can transact; the recipient must explicitly approve the posting; before approval, the amount continues to be recorded on the sender’s account; every balance change since account creation must be logged—transaction balance, voting balance, and dividend balance are recorded separately

The designated asset-holder entity can reconstruct the cap table on any historical snapshot
My take is that this doesn’t look like a technical document—it reads more like a securities compliance requirements checklist: regulatory constraints come first, then the code implementation order follows the opposite of most public chains

The most interesting part, I think, is that in the SMST structure, each node separately tracks the transferable balance, votable balance, and dividend-eligible balance—behind that is the design of shareholder rights
Tokens are not only a carrier of assets, but also of voting rights and dividend rights

The supporting functions also confirm this: CREATE for opening an account, SEND to initiate a transfer, ACCEPT for the recipient’s approval, SETTLE to settle according to the approval time, CLAIM to reclaim after the other party refuses and the request expires—plus VOTE voting and PUSH DIVIDEND where the contract directly pushes dividends

Note that it’s pushing, not claiming. Compliance actions are all embedded into the contract workflow; it relies on code rather than human judgment

The whitepaper’s related research section also does its own horizontal comparison: Tezos adds only limited anonymity at the smart-contract layer, while Polymesh moves some privacy features off-chain

Findora’s on-chain privacy support is similarly limited. Dusk’s approach is to push the whitelist, the approval flow, and shareholding records entirely into the protocol layer, using zero-knowledge proofs to ensure the chain only shows validity—not the details
I think that difference is its real barrier in the compliance arena, not the four words “supports privacy”

Of course, my judgment has a premise: there are real issuance cases for tokenized securities, and the whitelist mechanism requires issuers to be willing to cooperate with operations. If, on-chain, the asset, voting, and dividend functions are left unused for the long term, then even a complete design like this is just idle
Watch the actual deployment of the XSC standard—look at the securities that are genuinely issued

$DUSK #dusk

After watching the PoS chain for a while, you’ll notice a public secret: how much the validating node is staking, and how much block-production weight it has
The entire network can see the funding scale completely exposed, and whales are watching each other—running the show on-chain is basically playing with the lights on
The whitepaper of @Dusk also hides this layer, and it doesn’t just hide the transaction layer—it hides the consensus layer too

First, my overall assessment: it falls a bit closer to Monero and Zcash
The whitepaper itself has also laid out prior people’s concerns—analysis of Bitcoin’s transaction graph has long been proven to be de-anonymizable; privacy coins solve transaction privacy, but they don’t solve transparent staking; Algorand achieves near-instant finality, but its committee of over two thousand and block certificates are simply too heavy

Dusk’s idea is to get all three: privacy, instant finality, and lightweight participation

The core mechanism is consensus SBA
It breaks into two roles: block producers and a committee. Block-making power is determined by Proof-of-Blind Bid: the staked amount is obscured using Pedersen commitments, and then the block producer uses PLONK zero-knowledge proofs to prove eligibility—both identity and amount remain invisible throughout

The whole process runs through three phases: generation, reduction, and protocol. When honest staking accounts for more than two-thirds, finality approaches instant, and the probability of forks can be ignored

I think the clever part is that it changes the attacker’s cost calculation—you can’t see who is staking or how much, so the attack cost becomes a black box
To do harm you can only make blind guesses, and that in itself is an additional layer of security

The transaction layer uses a dual-track design
Phoenix handles UTxO privacy transactions, together with stealth addresses; the anonymity set grows as transaction volume increases; Zedger handles compliance, using private accounts based on sparse Merkle segment trees. The account owner only needs to publicly disclose the change in the root hash; along with whitelisted transactions and recipient confirmation, the issuer can also reconstruct the equity structure at any historical time point

Regulatory requirements for tokenized securities are written into the protocol line by line

Of course, my assessment has a premise: tokenized securities really need to take off, and on-chain asset volume has to grow. If policies squeeze from both sides and the narrative stays dormant for the long term, the logic won’t hold

My recommendation: don’t chase narratives—watch the rollout data. Focus on the number of assets, the number of active provisioners, and the total amount staked

$DUSK #dusk