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Etherum Smart Contracts Security improvement using machine learning techniques CS619 Final Project Fall 2020

Etherum Smart Contracts Security improvement using machine learning techniques CS619 Final Project Fall 2020

Etherum Smart Contracts Security improvement using machine learning techniques

 

Project Domain / Category

 

Machine Learning

 

Abstract / Introduction

 

Ethereum is a decentralized open source blockchain featuring smart contract functionality. Ether is the native cryptocurrency token of the Ethereum platform. It is the second-largest cryptocurrency by market capitalization, behind Bitcoin. Smart contracts are code files written in programming language named solidity, as the block chain is based on smart contract, so the security of smart contract is very important and vital to the security of blockchain system itself. Smart contracts can have many vulnerabilities like recursive calls, unpredictable ether flows, Suspected input, transaction reordering and insecure code patterns. Our goal in this project is to detect these vulnerabilities.

 

Functional Requirements:

  • The system must be able to analyse a complete solidity code file (smart contract).

 

  • System will use machine learning techniques to check for vulnerabilities in the smart contract submitted.

 

  • System can check any 3 vulnerabilities from the given data set.

 

  • Deploying smart contract on ehterum network is not required.

 

The following flow can be followed to classify unsafe code (vulnerable code) and safe code of a smart contract.

 

Tools: Any Modern programing tool (Python recommended)

 

DataSet:

 

https://github.com/smartbugs/smartbugs/tree/master/dataset

 

 

 

Supervisor:

 

Name: Bilal Bin Umar

Email ID: bilal.umar@vu.edu.pk

Skype ID: u.bilal

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