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@article{187215,
author = {Mohammed Adin Khan and MS.SURABHI CHAVHAN and Siddhesh Lanjewar and Harsh Chaudhari and Mustakimuddin Sheikh and Mohammed Taufik Sheikh and Vikrant Buggewar},
title = {BLOCKCHAIN SECURITY ENHANCEMENT: TO DETECT SMART CONTRACT VULNERABILITIES},
journal = {International Journal of Innovative Research in Technology},
year = {2025},
volume = {12},
number = {6},
pages = {4881-4885},
issn = {2349-6002},
url = {https://ijirt.org/article?manuscript=187215},
abstract = {Blockchain technology has emerged as one of the most significant innovations of the 21st century, offering transparency, decentralization, and secure record keeping. Its promise lies in eliminating intermediaries and ensuring that transactions are immutable and verifiable. However, while the blockchain framework itself is robust and secure, the smart contracts that operate on top of it are often vulnerable due to logical flaws or programming mistakes. These vulnerabilities can be exploited by attackers, leading to loss of funds, system disruptions, and reputational damage.
This project, titled “Blockchain Security Enhancement: To Detect Smart Contract Vulnerabilities,” introduces a comprehensive framework designed to detect and mitigate weaknesses in smart contracts. The framework uses a combination of static analysis, dynamic analysis, and artificial intelligence to identify issues such as reentrancy, integer overflow, timestamp dependency, and unauthorized access before deployment on a live blockchain.
The proposed system, implemented using Python, Solidity, and machine learning tools integrated with the Ethereum test network, provides automated vulnerability detection with real-time reporting and a user-friendly web interface. Experimental results on a dataset of 100 smart contracts show a detection accuracy of 92% and an average analysis time of 3.5 seconds per contract. The findings demonstrate that the system is efficient, accurate, and practical for developers building modern decentralized applications (DApps).},
keywords = {},
month = {November},
}
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