Jeeya_Awan

While Zcash and Monero pioneered personal privacy with groundbreaking tech like zk-SNARKs and ring signatures, they weren't built for the complex demands of regulated financial markets. Traditional finance needs more than just hidden transactions; it requires:
• Clear regulatory frameworks
• Auditable privacy (selective disclosure to authorities)
• Confidential smart contracts for complex deals
Dusk Network integrates these crucial features, making it the blockchain where privacy meets compliance head-on. We're building the infrastructure for the next generation of regulated digital assets.
Let's understand this with a practical example: A Private Equity Fund on the Blockchain.
Let's imagine "Evergreen Capital," a private equity firm, wants to tokenize units of its new fund to 100 accredited investors.
• On Monero/Zcash: They could send tokens to investors, but they couldn't prove to the government who owns what, couldn't automate the 2% management fee, and couldn't stop an unauthorized person from buying into the fund.

• On Dusk: The fund is invisible to competitors. However, the blockchain automatically checks every buyer's digital "clearance" before a trade completes. At the end of the year, the firm gives the auditor a View Key, and the auditor confirms the fund is legal in seconds.
@Dusk #Dusk $DUSK

@Dusk is a Layer-1 blockchain specifically engineered to solve the privacy-compliance paradox that prevents large financial institutions from using public blockchains like Bitcoin or Ethereum.
While public blockchains are transparent (anyone can see every wallet balance and transaction history), regulated finance requires privacy for trade secrets and transparency for regulators.
#Dusk uses advanced Zero-Knowledge Proofs (ZKPs); specifically a standard called PLONK—to allow users to prove they have the right to make a transaction without revealing their identity, balance, or the amount being sent.
Unlike Ethereum, where privacy is often an optional "add-on" (Layer 2), Dusk builds privacy into its core Virtual Machine (Rusk). It provides:
✓ Confidentiality: Transaction details are hidden from the public.
✓ Auditable Privacy: Issuers can still grant regulators specific access to audit data to meet KYC/AML requirements.
✓ Finality: Transactions are final instantly, which is a legal requirement for securities trading that Bitcoin (which uses probabilistic finality) cannot meet.

Let me you understand this with a practical example, that is Tokenized Corporate Bonds:
Imagine a company, "GlobalCorp," wants to issue $100 million in digital bonds to 500 private investors.
I've created a tables for your better understanding:

I've compared how Dusk acts as the middle ground between the total transparency of Bitcoin/Ethereum and the Total Opacity of private banking systems.

$DUSK

Tehnologia blockchain, cu descentralizarea și securitatea sale intrinsecă, a deschis noi orizonturi în diverse domenii, în special pe piața financiară. Cu toate acestea, o problemă persistentă rămâne: cum să integreze armonios transparența cu confidențialitatea, în special atunci când se manipulează date financiare sensibile. Rețeaua Dusk apare ca o soluție convingătoare, introducând un protocol blockchain conceput cu grijă pentru piețele financiare reglementate, oferind un echilibru subtil între confidențialitate, conformitate și scalabilitate, esențial pentru instituțiile financiare tradiționale.

@Walrus 🦭/acc focuses on reliability and trust. It ensures that even if the computers running the network change (nodes leaving/joining) or if someone tries to upload fake data, the system remains stable and honest.
I will give the practical example of "The Handover". Imagine a digital library where the staff (storage nodes) changes every 24 hours. This change is called an Epoch Change.
• The Problem (Churn): In most systems, when the old staff leaves and new staff arrives, there is a blackout period where you can't borrow books because the new staff is still organizing the shelves.
• The Walrus Solution: It uses a multi-stage transition. The Old Committee stays active while the New Committee is being set up. They pass the data baton smoothly so that users can still upload and download files without even noticing the staff change.
Let's take a look at defending against "Malicious Clients";
Walrus uses Authenticated Data Structures.
• Example: If a user tries to upload a file but intentionally omits a few pieces to break the system, the system detects it immediately.
• Why it matters: It prevents a bad actor from wasting the network's storage space or corrupting the data that other people are trying to read.
I also observed the performance at scale (Graph) and experimental evaluations show that as the number of nodes increases, Walrus doesn't slow down like traditional blockchains. Instead, its performance remains steady because of how it handles data.

To understand how Walrus handles Epoch Changes and Scaling practically, I'm giving you a concrete example and the data visualized in the graphs.

The first one was practical example of the Handover Transition.
Take a decentralized video streaming app as an example using Walrus. The network undergoes an Epoch Change (every week, the set of storage nodes is updated based on staking).
• The Scenario: At 12:00 PM on Sunday, the Old Committee (100 nodes) is scheduled to be replaced by the New Committee (100 nodes, some different).
• Traditional Failure: In older systems, the network might pause for several minutes to sync data, meaning a user watching a video would see a "Loading..." spinner or a 404 error during the switch.
• The Walrus Solution: Walrus uses a multi-stage transition. From 11:55 AM to 12:05 PM, both committees are active.
• Writes go to both.
• Reads can come from either.
• Result: The user watching the video never sees a glitch.
Now let's visualize the benefits;
1. Availability During Churn:
As I've shown you in the availability during Node Churn graph:
• Traditional Systems (Red): Experience a blackout or a massive drop in reliability during transitions because they haven't solved the synchronization problem during node swaps.
• Walrus (Green): Maintains a flat line of near-perfect availability. The Multi-stage protocol ensures that data is always reachable, even while the staff is changing.
2. Performance at Scale:
As I've shown you in the performance at Scale graph:
• Traditional Systems (Red): Often suffer from "coordination bloat." The more nodes you add, the more they have to talk to each other to stay in sync, which causes latency (delay) to skyrocket.
• Walrus (Green): Because of its decentralized architecture and authenticated data structures, adding more nodes doesn't slow it down significantly. It achieves practical performance, meaning it stays fast enough for real-time apps even as the network grows to hundreds or thousands of nodes.
#Walrus $WAL

Red stuff este nucleul lui Walrus, folosește o grilă matematică bidimensională pentru a oferi o securitate ridicată cu costuri reduse de stocare, permițând sistemului să se autorepare prin descărcarea doar a unei fracțiuni mici de date care au fost efectiv pierdute.
(𝑂(|𝑏𝑙𝑜𝑏|/𝑛) în comparație cu 𝑂(|𝑏𝑙𝑜𝑏|) în sistemele tradiționale).
Această afirmație descrie eficiența de bază și avantajul matematic al protocolului Red Stuff.
Pentru a înțelege de ce acesta este un superputere pentru stocarea descentralizată, am descoperit cum rezolvă problema benzii de reparație. Problema este de ce sistemele tradiționale se panică?

#Walrus este conceput pentru a gestiona obiectele binare mari (blobs) în mod mai eficient decât stocarea tradițională pe blockchain sau rețelele descentralizate existente precum IPFS sau Filecoin.
Să vedem cum este corectă această afirmație; după părerea mea, primul punct este problema compromisului. În sistemele distribuite, de obicei trebuie să alegi două dintre următoarele: cost scăzut, încredere ridicată sau viteză mare. Al doilea punct este replicarea completă, fiecare nod păstrează o copie. Aceasta este foarte sigură, dar extrem de costisitoare, de exemplu, stocarea unui GB costă prețul pentru 1.000 GB dacă există 1.000 de noduri. Iar al treilea punct este codificarea simplă prin erori, care împarte datele în fragmente. Aceasta economisește spațiu, dar de obicei necesită o cantitate masivă de lățime de bandă pentru a reconstrui fișierul dacă câteva noduri devin inaccesibile.