Advancing Bug Detection in Solidity Smart Contracts with the Proficiency of Deep Learning
Syam Machinathu Parambil Gangadharan, Chandrakala Arya, Srinivas Aluvala, Jagendra Singh, Prabhishek Singh, Ashok Murugesan
Abstract
Smart contracts have the potential to revolutionize many sectors by automating difficult procedures and removing the need for middlemen. Smart contracts are self-executing contracts in which the contents of the agreement between the buyer and seller are directly encoded into lines of code. Nevertheless, because smart contracts are immutable, vulnerabilities cannot be easily rectified after they are implemented. For this reason, it is essential to identify and eliminate vulnerabilities before implementation. The Ethereum Blockchain is the primary home of such Contracts which are written in the full-fledged programming language-Solidity. The process of finding these vulnerabilities before deployment is known as Smart Contract Auditing. We propose this new scalable framework of Smart Contract Auditing which promises accuracy and dependability using Deep Learning approaches that can be leveraged for large scale auditing.