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@article{169559,
        author = {SHAIK SHAHINA and D MURALI},
        title = {PHISHING WEBSITE DETECTION},
        journal = {International Journal of Innovative Research in Technology},
        year = {2024},
        volume = {11},
        number = {6},
        pages = {1256-1260},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=169559},
        abstract = {Online phishing is one of the most common attacks on the modern internet. The goal of phishing website uniform resource locators is to steal personal data including login credentials and credit card numbers. As technology keeps growing, phishing strategies began to develop rapidly. Machine learning built an effective device used to attempt phishing attacks. In this project, we have built a phishing website by using fast API. We have used two so many different libraries and two algorithms which are logistic regression and multimodal NP. The purpose of this project is to check whether phishing websites are good URLs or bad URLs. We gathered data to create a dataset of malicious links and curate it for the machine learning model.},
        keywords = {Phishing, Detection, API, URLs, Machine learning models, logistic regression.},
        month = {November},
        }