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Adversarial Analysis of Malicious URLs by yasokrishna178 is a document available to read on EtoBox.

This paper analyzes a malicious advertisement URL detection framework using machine learning techniques, focusing on the extraction of novel lexical and web-scraped features. The study evaluates the performance of four classifiers and achieves a high detection accuracy of 99.63% while addressing vulnerabilities against adversarial attacks. The research highlights the importance of effective feature extraction and the challenges posed by evolving malicious URL tactics.

Author

yasokrishna178

Language

EN