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@article{178977,
        author = {Manchala Beula Grace},
        title = {Verification of smart contracts using Machine Learning},
        journal = {International Journal of Innovative Research in Technology},
        year = {2025},
        volume = {11},
        number = {12},
        pages = {7196-7205},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=178977},
        abstract = {This paper offers a machine learning approach based on behavioral analysis to identify Ethereum smart contract vulnerabilities and fraud. The Random Forest model performed better than existing tools and other ML models, with accuracy of more than 90% and high interpretability. Features such as Ether value and number of transactions were significant in the identification of risks. This method advances blockchain trust and security, with added benefits for developers, auditors, and investors.},
        keywords = {},
        month = {May},
        }