Abstract
Web URLs are the base for Internet to locate resources uniquely on the Internet. Recent report from poloalto networks states that more 86 thousand malicious URLs were registered during the Covid period between March and April 2020. Cyber-attacks through malicious URL causes lose more than billion in every year. Attacks through malicious URL are the handy way for the cyber-criminals. Systematic approaches are required to detect the malicious URL to prevent the cyber-attacks. Researchers proposed several techniques to detect the malicious URL. But it requires continuous efforts to block newly generated attacks. This paper presents overview of malicious URL detection techniques and recent research works and the issues. Also highlights the research challenges in malicious URL detection, which can help for the future researchers to bring out new solutions.
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Pradeepa, G., Devi, R. (2022). Review of Malicious URL Detection Using Machine Learning. In: Ranganathan, G., Fernando, X., Shi, F., El Allioui, Y. (eds) Soft Computing for Security Applications . Advances in Intelligent Systems and Computing, vol 1397. Springer, Singapore. https://doi.org/10.1007/978-981-16-5301-8_7
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DOI: https://doi.org/10.1007/978-981-16-5301-8_7
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