How crypto retail investors use FHE: Making money in the cryptocurrency space through DeFi trading agents.
How crypto retail investors can leverage Fully Homomorphic Encryption (FHE) to profit through DeFi trading agents in the cryptocurrency sector. This article will provide a specific, actionable guide for crypto retail investors, focusing on the use of FHE-based privacy-protecting DeFi trading agents to trade on Uniswap (a decentralized exchange in the Ethereum ecosystem), protecting trading strategies and fund privacy while earning profits through automated trading. I will simplify technical details from the retail investor's perspective, providing specific cases, steps, tools, profit models, and risk management suggestions to ensure the content is understandable and practical. The cases will be based on Ethereum Layer 2 (like Polygon) to reduce gas fees, combined with real-world examples to support.
How crypto retail investors use FHE: Making money in the cryptocurrency space through DeFi trading agents.
Fully Homomorphic Encryption (FHE) is a cryptographic technique that allows computations on encrypted data, providing crypto retail investors with a powerful tool to protect trading privacy. In decentralized finance (DeFi), retail investors trade on platforms like Uniswap, but the public nature of on-chain data may lead to trading strategies being front-run or analyzed. FHE-based DeFi trading agents (AI smart agents) can automate trade execution, optimize strategies, and protect user data privacy. This article uses retail investors using FHE-based Uniswap trading agents as a case study to detail how to set up, operate, and profit, helping retail investors gain a competitive advantage in the cryptocurrency market.
1. Retail investors using FHE trading agents:
1. Scenario description
Goal: As a crypto retail investor, you want to trade on Uniswap (like buying ETH/USDC) while optimizing trading prices and slippage through an AI smart agent, protecting trading data (like order amounts and target prices) from being publicly disclosed on-chain.
Retail investor demand:
Privacy protection: Prevent trading strategies from being analyzed by miners, bots, or other traders, avoiding front-running.
Automated trading: Utilize AI agents to automatically execute trades based on market trends (e.g., price fluctuations), saving time.
Low cost: Operate on Ethereum Layer 2 (like Polygon) to reduce gas fees.
Simple and easy to use: No deep technical knowledge required, operated through user-friendly interfaces (like the MetaMask plugin).
FHE Role:
Encrypted trading data (like purchase amounts), AI computes the best trading path in the encrypted domain.
Only users can decrypt transaction results, ensuring privacy.
Profit model:
Earn the spread by optimizing trades (such as low slippage and high yield).
Participate in token incentives or dividends from the platform.
2. Retail investor pain points:
On-chain transactions are transparent, making them vulnerable to high-frequency trading bots, leading to slippage losses (price deviations).
Manual trading is time-consuming, making it difficult for retail investors to monitor the market in real-time.
Privacy breaches may lead to strategy replication or account tracking.
FHE advantages:
Encrypted trading data to prevent front-running and strategy leaks.
AI automates trading to increase yield.
Enhance trust and comply with privacy regulations (like GDPR).
Market potential:
Uniswap's daily trading volume is about $1 billion, with retail investors accounting for over 60% (data source: Dune Analytics).
Privacy-protecting trading agents can attract retail investors, with an expected market penetration growth of 10% annually.
2. Specific applications of FHE in DeFi trading agents
Here are specific scenarios where retail investors use FHE trading agents on Uniswap:
Automated trading with privacy protection:
You input trading parameters (like buying 0.1 ETH at a target price of $2000), and the data is encrypted via FHE.
AI agents analyze Uniswap pool prices on encrypted data, calculating the best trading path (e.g., ETH → USDC).
Generate encrypted orders; after on-chain execution, you decrypt the results to confirm the transaction is complete.
Prevent front-running:
Encrypted order data prevents miners or nodes from gaining early access, reducing front-running risk.
Off-chain compute orders to reduce on-chain exposure time.
Personalized strategy optimization:
AI optimizes slippage, gas fees, or batch trading based on your historical trades (encrypted storage).
Your private data is not leaked, ensuring account security.
3. How retail investors use FHE trading agents: Steps to operate
Here are specific steps designed for crypto retail investors, assuming you are using an existing FHE trading agent platform (like a privacy trading DApp based on Uniswap). The steps are simplified to ensure no programming knowledge is required.
1. Prepare tools and accounts
Essential tools:
MetaMask: Encrypted wallet to manage ETH/USDC and FHE keys.
Polygon network: Ethereum Layer 2 with low gas fees (about $0.01/transaction).
FHE trading DApp: Assume using the fictional 'PrivacyTrade' DApp (similar to Zama's fhEVM project), providing FHE trading agents.
Preparation steps:
Install MetaMask:
Download the MetaMask browser extension (metamask.io).
Create a wallet, back up the mnemonic phrase, and deposit 0.1 ETH and 100 USDC (approximately $300).
Switch to Polygon network:
Add the Polygon mainnet in MetaMask (RPC URL: https://polygon-rpc.com).
Transfer ETH/USDC from Ethereum to Polygon via the Polygon bridge (wallet.polygon.technology) with a bridge fee of about $5.
Access PrivacyTrade DApp:
Open the DApp website (assumed to be privacytrade.io).
Connect MetaMask and authorize the Polygon account.
2. Set up the FHE trading agent
Operation:
Obtain FHE keys:
In the PrivacyTrade DApp, click 'Generate FHE Key' to generate a public/private key pair.
MetaMask automatically stores private keys; public keys are used to encrypt trading data.
Input trading parameters:
Enter the following in the DApp interface:
Trading pair: ETH/USDC.
Amount: Buy 0.1 ETH.
Target price: $2000 (±5% slippage).
Strategy: Automatic optimization (AI selects the best pool and timing).
The DApp uses FHE public keys to encrypt data and generate encrypted orders.
Confirm transaction:
MetaMask pops up a prompt to pay gas fees (about $0.01) and DApp service fees (about $0.50).
Click 'Confirm' to submit the order to the off-chain FHE computing node.
3. AI agents execute trades
Backend processes (no retail investor operation required):
Encrypted computing: The DApp's AI agents run FHE models off-chain (AWS Lambda + NVIDIA A100 GPU), analyzing Uniswap V3 pool prices to compute the best trading path.
On-chain execution: AI generates encrypted orders, uploads them through Chainlink oracles, and calls Uniswap smart contracts to execute trades.
Result returned: Encrypted trading results are stored on the Polygon chain, and you decrypt them via MetaMask.
User experience:
You see the trading results on the DApp interface (like buying 0.1 ETH at an actual price of $1995, saving $0.50 in slippage).
The entire process takes about 5 seconds, similar to a regular Uniswap trade.
4. Monitor and optimize
Operation:
View transaction history in PrivacyTrade DApp (encrypted storage, only you can decrypt).
Adjust strategies (e.g., set higher slippage tolerance or batch trading).
Enable 'automatic trading' mode, allowing the AI agent to monitor the market and check prices every hour.
Tools:
The DApp provides price charts (integrating Chainlink price data).
MetaMask notifies the trading status.
5. Withdraw profits
Operation:
Check USDC or ETH balance in MetaMask to confirm trading profits.
Transfer funds back to the Ethereum mainnet via the Polygon bridge, or continue trading on Polygon.
Example:
You bought 0.1 ETH for $1995, and after a week, the price rose to $2100, selling for a profit:
Profit = 0.1 * ($2100 - $1995) - $0.51 (fees) = $10.49
6. Participate in platform incentives
Operation:
PrivacyTrade issues governance tokens (like TRADE); holding tokens enjoys service fee discounts (0.5% → 0.3%).
Stake TRADE tokens in the DApp to earn an annual reward of 10%.
Participate in community votes to decide platform features (like new trading pairs).
Example:
Stake 1000 TRADE (worth $100), with monthly earnings of $0.83 (10% annualized / 12).
4. Specific profit models
The following are strategies for retail investors to make money through FHE trading agents, combined with market data:
Trading spread:
Model: Use AI to optimize trading, reduce slippage and gas fees, and earn profits from price fluctuations.
Potential: Assuming 5 trades per week, saving $0.50 in slippage each time, monthly profit:
$0.50 * 5 * 4 = $10
If the market rises (e.g., ETH rises from $2000 to $2200), the profit from a single trade:
0.1 * ($2200 - $2000) - $0.51 = $19.49
Implementation: Enable the DApp's 'low slippage' mode and set a 3% slippage tolerance.
Token incentives:
Model: Hold or stake PrivacyTrade's TRADE tokens to enjoy discounts or rewards.
Potential: Stake 1000 TRADE ($100), with an annual yield of 10% ($10) and a token appreciation potential of 50% ($50).
Implementation: Buy TRADE on Uniswap, operate on the DApp staking page.
Arbitrage opportunities:
Model: AI agents identify price discrepancies between Uniswap and SushiSwap to execute arbitrage trades.
Potential: Single arbitrage profit of 0.5%-1% (approximately $1-$2/trade), two times a week, monthly profit:
$1.50 * 2 * 4 = $12
Implementation: Enable the DApp's 'arbitrage mode' to monitor multiple DEXs.
Long-term investment:
Model: Use FHE to protect privacy and safely participate in DeFi investments (like providing liquidity).
Potential: Provide ETH/USDC liquidity on Uniswap, with an annual yield of 15% (approximately $45/year on a $300 investment).
Implementation: Connect to Uniswap pools in the DApp and encrypt liquidity data.
5. Case reference
Here are similar cases in the real world that support the feasibility of the proposal:
Zama fhEVM:
Zama develops an FHE-optimized Ethereum Virtual Machine to support private DeFi transactions.
Application: Privacy-protected orders attract both retail and institutional investors.
Insight: FHE has a mature path to implementation in DeFi.
1inch:
1inch provides a DEX aggregator to optimize trading paths and reduce slippage.
Application: Combining FHE can enhance privacy, attracting retail investors.
Insight: There is market demand for AI-optimized trading.
Chainlink CCIP:
Chainlink supports off-chain computing on-chain, similar to off-chain encrypted computation in FHE trading agents.
Insight: The off-chain + on-chain mixed model can reduce costs.
6. Risks and response strategies
Market risks:
Issue: Cryptocurrency prices are highly volatile, which may lead to losses.
Response: Set stop losses (the DApp supports automatic sales below $1900) and diversify investments (ETH, USDC).
Technical risks:
Issue: FHE DApp may have bugs or delays.
Response: Choose audited platforms (like PrivacyTrade audited by CertiK) and test with small trades.
Front-running risk:
Issue: Even with FHE, on-chain execution may be front-run.
Response: Enable the DApp's 'fast execution' mode to prioritize off-chain computation.
Regulatory risks:
Issue: Privacy trading may trigger AML reviews.
Response: Choose KYC-compliant DApps and keep transaction records.
7. Cost and revenue analysis
Initial cost:
Funds: 0.1 ETH + 100 USDC (approximately $300).
Bridge fee: $5 (Ethereum → Polygon).
Service fee: $0.50/trade, $10 per month (20 trades).
Total: $315.
Expected returns:
Trading spread: $10-$20 per month (optimized slippage + market rise).
Arbitrage: $12 per month.
Token rewards: $0.83 per month (1000 TRADE staked).
Total: $22.83-$32.83 per month, annualized return rate of 87%-125% (on a $315 investment).
Break-even: About 2 months (assuming stable returns).
8. Future opportunities
Layer 2 Popularization: Polygon and Arbitrum reduce gas fees, promoting retail adoption of FHE trading.
Privacy demand: Growing concern among retail investors for privacy protection, making FHE agents mainstream.
Web3 ecosystem: FHE can be expanded to NFT and metaverse trading, increasing profit opportunities for retail investors.
9. Conclusion
Crypto retail investors can achieve privacy-protected automated trading on Uniswap through FHE-based DeFi trading agents (like PrivacyTrade DApp), optimizing slippage, preventing front-running, and earning profits. Specific steps include setting up MetaMask and Polygon network, inputting encrypted trading parameters through the DApp, allowing AI agents to execute trades, monitoring earnings, and participating in token incentives. Profit paths include trading spreads (monthly $10-$20), arbitrage (monthly $12), and token rewards (monthly $0.83), with annualized return rates reaching 87%-125%. With the successful experiences of cases like Zama and 1inch, retail investors can leverage FHE trading agents to gain a competitive advantage in the DeFi market.
Action plan:
Get started immediately: Download MetaMask, deposit $300, and switch to the Polygon network.
Test trade: Make a small trade (0.01 ETH) in the PrivacyTrade DApp to verify effectiveness.
Optimize strategies: Enable 'arbitrage mode' and 'automatic trading', checking earnings weekly.
Community participation: Join the DApp Discord to get the latest features and token airdrops.
#MindNetwork全同态加密FHE重塑AI未来 This issue participates in the Binance writing competition. Thank you all for reading so diligently. Also, I have good news: a project I previously mentioned for airdrop is about to launch its token 😀