Finding Ethereum Smart Contracts Security Issues by Comparing History Versions

TL;DR

This paper introduces a deep learning approach to identify security issues in Ethereum smart contracts by tracking their version history and analyzing updates for vulnerabilities.

Contribution

It presents a novel method combining deep learning and open card sorting to detect security issues through contract version comparison.

Findings

Successfully identified security issues in smart contract updates

Demonstrated effectiveness of deep learning in contract version analysis

Provided a new approach for proactive security vulnerability detection

Abstract

Smart contracts are Turing-complete programs running on the blockchain. They cannot be modified, even when bugs are detected. The Selfdestruct function is the only way to destroy a contract on the blockchain system and transfer all the Ethers on the contract balance. Thus, many developers use this function to destroy a contract and redeploy a new one when bugs are detected. In this paper, we propose a deep learning-based method to find security issues of Ethereum smart contracts by finding the updated version of a destructed contract. After finding the updated versions, we use open card sorting to find security issues.