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Strengthening Smart Contracts to Handle Unexpected Situations

机译:加强智能合约以处理意外情况

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Decentralized application users may face unexpected situations that the smart contract implementing the application should handle, but cannot, because the smart contract cannot be modified once it is deployed. Therefore, we need 'stronger' smart contracts with flexible structures that are resilient in such unexpected situations. In this paper, we propose a generic mechanism to strengthen smart contracts and handle possible unexpected situations. Given a smart contract, this mechanism automatically generates an action list which offers actions as interfaces to change parameters of smart contracts and a voting system that utilizes a limited voter group randomly chosen from the peers. Each action in the action list can change a corresponding parameter of smart contracts. The actions, when approved by the majority, are executed to change the parameters. When users face unexpected situations in a transaction, they choose some actions as the solution and pass them to the voting system. Since a smart contract has finite parameters, there are finite actions. By arranging and combining these actions, our mechanism offers solutions that can handle wide-ranging unexpected situations. Also, to execute a solution, the majority of voters need to approve it, thus not violating the protocol of the original smart contract. Voters are rewarded based on quadratic rules for peer prediction, which makes telling true preferences the only way to maximize rewards. Using machine learning, we predict users' preferences based on the voting records. The predictions are provided as default values for future votes to avoid users' need to vote manually each time.
机译:分散的应用程序用户可能会遇到意想不到的情况,实现该应用程序的智能合约应处理这些意外事件,但不能处理,因为一旦部署智能合约就无法对其进行修改。因此,我们需要具有灵活结构的“更强”智能合约,这些弹性结构在此类意外情况下具有弹性。在本文中,我们提出了一种通用机制来加强智能合约并处理可能的意外情况。在给定智能合约的情况下,该机制会自动生成一个动作列表,该动作列表将动作提供为更改智能合约参数的接口,并使用从对等方中随机选择的有限选民组进行投票的系统。操作列表中的每个操作都可以更改智能合约的相应参数。当得到大多数人的认可时,将执行这些操作以更改参数。当用户在交易中遇到意外情况时,他们会选择一些操作作为解决方案并将其传递给投票系统。由于智能合约具有有限的参数,因此存在有限的操作。通过安排和组合这些动作,我们的机制提供了可以处理各种意外情况的解决方案。另外,要执行解决方案,大多数选民都需要批准它,从而不违反原始智能合约的协议。投票者是根据二次规则进行同伴预测而获得奖励的,这使告诉真实偏好成为最大化奖励的唯一方法。使用机器学习,我们根据投票记录预测用户的偏好。这些预测是作为将来投票的默认值提供的,以避免用户每次需要手动投票。

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