The role of artificial intelligence in the audit automation of smart contracts
In recent years, the financial and trade world has experienced significant technology achievements, in particular with regard to artificial intelligence (AI). One of the areas that have a huge focus is the audit of a smart contract. In this article, we will delve into the automation of smart contract audits, its benefits and how it can be used to improve security and reduce the risk of error.
What are smart contracts?
Smart contracts are self -executing contracts with the terms of the contract written directly in the ranks of the code. Their goal is to create a more efficient and automated process for completing transactions, reducing the need for intermediaries and increasing transparency. However, as smart contracts are becoming more widespread, they also create significant security risks.
Problem: The audit of the smart contract
The audits of smart contracts are essential to ensure that these contracts comply with the regulatory standards and comply with the law. These audits can be time consuming, expensive and resource -intensive, and it is often necessary to manually review each code line. As a result, smart contract audits may be subject to errors or releases that can have serious consequences.
Artificial intelligence in smart contract audits
AI has become a promising tool for automation of smart contract audits. Using machine learning algorithms and natural language processing (NLP), these systems can analyze large quantities of code and determine possible vulnerabilities, including security flaws and regulatory inconsistencies.
Some of the main benefits of AI use in the smart contract audit are:
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Speed : AI -powered audit tools can perform audits much faster than human auditors.
- accuracy: Machine learning algorithms can analyze complex code fragments with high accuracy by reducing the risk of error or release.
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Scalability: AI systems can be trained on large data sets, making them ideal to simultaneously revise a number of smart contracts.
- Cost Efficiency: By automating audit, companies can reduce audit costs and distribute resources more efficiently.
As AI automates smart contract audits
AI -powered audit tools work through machine learning algorithms to analyze codes fragments and identify potential security risks. Here is a step -by -step process overview:
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Code Analysis: The AI system analyzes the fragment of the code and obtains appropriate data such as keywords, syntax and semantics.
- vulnerability identification: Machine learning algorithms use these extracted data to identify potential vulnerabilities, including security shortcomings and regulatory inconsistencies.
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Risk Assessment: The AI system assesses the risks identified and assigns the number of points based on their possibility and impact.
- Generation of the Audit Report: Based on a risk assessment, the AI system generates an audit report describing the identified risks and recommended rehabilitation measures.
AI real world applications in smart contract audit
AI -powered audit tools are used in a variety of sectors, including finances, energy and healthcare. Some examples are:
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Ripple: Ripple, Blockchain -based company, has been developed with a AI -powered smart contract audit tool that can audit up to 100 contracts per hour.
Hashgraph **: The distributed ledger technology company hashgraph has used machine learning algorithms to automate its smart contract audit, reduce costs and improve accuracy.
Conclusion
Artificial Intelligence (AI) transforms the smart contract to the audit landscape, offers significant benefits to speed, accuracy, scalability and profitability.