Cloudy (✱,✱)

It is a great honor to witness the @FlutonIO community continuing to thrive. Another 12 members have officially taken on the "Encrypted" role in recognition of their outstanding contributions. Congratulations to you all! I believe that with perseverance and commitment, every member of the community will achieve significant milestones. Keep up the consistent spirit. @cryptoperseus_

Why FHE Is a Critical Foundation for Fluton’s Confidential DeFi Vision DeFi has introduced new ways to access financial services onchain, but most of these interactions still happen in public. Transactions can be tracked, balances can be analyzed, and execution strategies often become visible to anyone monitoring the network. While transparency helps with verification, it can also expose sensitive information that users, businesses, and automated systems may prefer to keep private. For Fluton, solving this problem requires more than simply encrypting data before it is stored or transferred. Confidential execution depends on the ability to process information without exposing it during computation. This is where Fully Homomorphic Encryption (FHE) becomes a key part of the architecture. FHE allows computation to happen directly on encrypted data, meaning inputs can remain protected while logic is applied and intermediate values stay hidden throughout execution. Fluton uses this capability to support encrypted intents and confidential execution flows. Users describe desired outcomes through encrypted intents, while solver networks execute actions on encrypted state. Sensitive information such as balances, transaction amounts, routing preferences, and execution strategies does not need to become public for the action to be completed. Privacy remains active throughout submission, routing, execution, and settlement, creating a different model from the fully transparent execution commonly found in DeFi today. This is why FHE is more than a supporting technology within Fluton's design. It is one of the foundations that makes confidential DeFi possible. The ability to compute on encrypted data enables private-by-default execution across payments, swaps, bridging, and yield strategies while helping protect the information that would otherwise be exposed on public infrastructure. By building around FHE, Fluton is working toward a model where DeFi can remain programmable without requiring every aspect of financial activity to be publicly visible. @FlutonIO

Fluton Research Series 6/20: Privacy as MEV Protection In Post 5, I explored how @FlutonIO can compute on encrypted data without exposing it. That privacy has another important consequence: It can reduce the information available to MEV extractors. Most people experience MEV without realizing it. You submit a trade. Before it settles, bots can detect its size, direction, slippage tolerance, and likely market impact. That information creates opportunities for front-running, sandwich attacks, back-running, and strategy copying. The problem is not only that transactions are public after execution. They are often visible while still waiting to be executed. Your pending transaction becomes a signal. Fluton attempts to remove that signal through encrypted intents. The user’s desired action is encrypted before it enters the execution flow. Solvers can compete to fulfill the intent without receiving its sensitive plaintext parameters, while the user chooses between offers based on priorities such as cost or speed. This changes the information structure. A solver may know that an opportunity exists. But it should not automatically know the private details needed to exploit the user. That distinction matters because many MEV defenses try to repair execution after transaction data has already leaked. Fluton’s approach is more fundamental: Prevent the valuable information from becoming public in the first place. Privacy therefore becomes more than personal secrecy. It becomes execution protection. The less the network can observe about an unfinished action, the harder it becomes to trade against that action before settlement. Fluton’s documentation describes confidential execution as protecting strategy, size, routing preferences, and conditions throughout the action lifecycle. This does not mean every form of MEV disappears automatically. Solvers, pricing mechanisms, settlement rules, liquidity conditions, and implementation details still matter. But encrypted intents could remove one of MEV’s most important resources: Advance knowledge of what the user is about to do. In traditional markets, hiding an order until execution is considered normal protection. Onchain, Fluton is trying to make that protection programmable.

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Fluton Research Series 5/20: Computing Without Seeing Encrypted intents sound powerful, but they create an obvious question: How can a network execute an instruction it cannot read? This is where Fully Homomorphic Encryption, or FHE, enters @FlutonIO architecture. Traditional systems usually follow a familiar pattern: Encrypt the data. Decrypt it for processing. Encrypt it again afterward. That middle step is the weakness. The moment sensitive data is decrypted, someone, somewhere, may gain access to it. FHE changes that model. It allows computation to happen while the data remains encrypted. Imagine placing numbers inside a locked box. The network can perform calculations on that box and produce the correct result without opening it or seeing the numbers inside. Applied to DeFi, this could allow balances, transaction amounts, routing preferences, and trading conditions to remain hidden while smart contracts still process the action. That is why FHE matters to Fluton. Encrypted intents protect what the user wants. FHE helps the system act on that intent without first turning it back into public information. But this technology is not magic. FHE is computationally expensive, and practical performance remains one of its biggest challenges. Fluton’s approach appears to be selective rather than encrypting every piece of information without distinction. That trade-off will matter. The long-term winner in confidential DeFi may not be the protocol that encrypts the most data. It may be the one that finds the best balance between privacy, speed, cost, and usability. Fluton is betting that encrypted computation can eventually become invisible infrastructure. Users will not need to understand the mathematics. They will simply expect their financial data to remain private while their actions still work.