Electronic Voting System using Blockchain and Machine Learning

Abstract

Traditional voting systems suffer from several shortcomings, such as low voter turnout (this can be attributed to factors such as inconvenient polling locations, long wait times, and limited voting hours. Many eligible voters may be discouraged from participating due to these barriers, which can result in an incomplete representation of the electorate's will), and lack of voter anonymity (in some traditional voting systems, it can be challenging to ensure complete voter anonymity. For instance, in small communities, it may be possible to discern how individuals voted based on the order in which they cast their ballots or through visual cues. Lack of anonymity can lead to concerns about coercion or intimidation, as voters may fear retaliation for their choices.). Moreover, the centralized nature of these systems can lead to concerns regarding data integrity and privacy. These challenges undermine the democratic process and diminish public trust in election outcomes. The project aims to address these challenges by implementing an Electronic Voting System (EVS) using Ethereum based blockchain technology and incorporating it with the HAAR Cascade algorithm which will detect users with the aid of machine learning. All voting and user data that goes into the Blockchain is securely stored and can be retrieved to check for correctness in real time by the aid of smart contracts. Blockchain's inherent properties of transparency, immutability, and decentralization offer promising solutions to the problems plaguing traditional voting systems. By incorporating the proposed techniques, the suggested EVS will provide secure, tamper-proof vote storage and counting.