Authors : Nityay Kherde, Anushka Kale, Govind Kurup , Asmit Meshram ,Prof Leena Mandurakar DOI : 10.46335/IJIES.2024.9.7.17 Abstract- This paper presents a review of machine learning-based approaches for identifying and classifying malicious websites. Various studies have tackled this challenge by extracting features from URLs and website content to train machine learning models. Methods include lexical, host-based, […]
READ MOREAuthors :Pratiksha S. Patil , Nilesh Vani DOI : 10.46335/IJIES.2025.10.9.8 Abstract – The growing prevalence of phishing assaults, especially in online banking and e-commerce, calls for the creation of reliable detection systems. A thorough analysis of the use of machine learning methods for phishing website identification is presented in this research. By leveraging supervised classification […]
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