Opinion: Transaction Simulation Can Enhance Crypto Wallet Security

Vitalik Buterin, co-founder of Ethereum, has proposed the adoption of transaction simulation mechanisms in crypto wallets and smart contracts to boost user safety and streamline experiences. He argues that security and user experience are closely linked, emphasizing the need to align a user’s intentions with the system’s actions.

According to Buterin, the primary aim of security is to bridge the gap between a user’s desired actions and the actual operations of the system.

Buterin suggests that security architectures should prioritize user intent, creating systems capable of verifying actions before they are executed. This principle applies not only to Ethereum technologies but also to broader operating systems and hardware.

He envisions a scenario where users first express their desired action, review a simulated outcome, and then confirm or cancel the transaction.

Additional security measures could include setting spending limits and implementing multisignature protocols. A transaction should only be completed if three conditions are met: intent is clear, the expected outcome is understood, and the risk level is acceptable. Ideally, safe actions would be automated, while more complex or riskier transactions would necessitate further verification.

Complexities in Implementation

However, identifying user intent remains a significant challenge, which Buterin describes as highly intricate. He notes that achieving absolute security is unattainable, not due to human or machine errors but because understanding user intent is fundamentally difficult.

Buterin pointed out, “Absolute security is impossible... because the concept of user intent is fundamentally complex.”

He advocates for a system where users can express their intentions through multiple channels, with the system only responding when these inputs align. Buterin also sees potential in utilizing large language models (LLMs) as an additional layer to discern user intent, suggesting that when tailored to individual users, these models can closely mimic human reasoning.

He stated, “A typical LLM becomes a 'shadow' of the user, allowing for a nuanced understanding of what is normal behavior.”

This discussion also ties into Buterin's broader vision of integrating AI within the blockchain ecosystem.