1. Anti-Phishing Working Group(APWG). https://apwg.org/trendsreports/ (Published on 7 June 2022)
2. Do Xuan, C., Dinh Nguyen, H., Nikolaevich Tisenko, V.: Malicious URL detection based on machine learning. Int. J. Adv. Comput. Sci. Appl. 11(1), (2020)
3. Liu, C., Wang, L., Lang, B., Zhou, Y.: Finding effective classifier for malicious URL detection. In: Proceedings of the 2018 2nd International Conference on Management Engineering, Software Engineering and Service Sciences, pp. 240–244 (2018)
4. Ollmann, G.: The phishing guide understanding & preventing phishing attacks. NGS Software Insight Security Research (2004)
5. Ramya, K., Sharma, A., Mehta, K., Raj, V.: A comprehensive end-to-end framework for detection and prevention of cross site scripting attack