Fortifying E-Voting Privacy: A Triad of Blockchain, Convolutional Neural Networks, and Quantum Key Distribution for Unparalleled Security

Bhaumik Tyagi; Pratham Taneja; Avi Thakur1

1

Publication Date: 2023/08/18

Abstract: The advancement of blockchain has facilitated scholars to remodel e-voting systems for future generations. Server-side attacks like SQL injection attacks and DOS attacks are the most common attacks nowadays where malicious codes are injected into the system through user input fields by illicit users which leads to data leakage in the worst scenarios. Besides, Quantum attacks are also there which manipulate the transactional data between blocks in the blockchain. Stale Block and Blockchain forks are also one of the main issues in existing blockchain-led e-voting systems. In order to deal with all the above-mentioned attacks, integration of Blockchain, CNN & Quantum Key Distribution is done in this very research. In, e-voting systems the employment of blockchain technology is not a novel concept. But privacy and security issues are still there in public and private blockchains. To solve this, Blockchain, CNN & QKD-based proposed model is introduced in this research. This research proposed cryptographic signatures and blockchain smart contract algorithms to validate the origin and integrity of the votes. Also, a comparison between previous smart contract algorithms and proposed smart contract algorithms is done in terms of time complexity.

Keywords: Hybrid Blockchain, Secure e-Voting System, Convolutional Neural Networks, Quantum Key Distribution.

DOI: https://doi.org/10.5281/zenodo.8262592

PDF: https://ijirst.demo4.arinfotech.co/assets/upload/files/IJISRT23AUG782.pdf

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