Publication Type : Book Chapter
Publisher : Springer
Source : In Advances in cyber security analytics and decision systems (pp. 27-56). Springer, Cham.
Url : https://www.researchgate.net/publication/338409334_Dynamic_Recognition_of_Phishing_URLs_Using_Deep_Learning_Techniques
Campus : Chennai
School : School of Engineering
Department : Computer Science and Engineering
Year : 2020
Abstract : Phishing is a critical issue that faces the digital security. The straightforwardness of the web and Internet uncovered open doors for offenders to transfer malevolent substance at the same time with the upgrade of online business trades, for example, phishing – the demonstration of taking individual data which ascends in number. Internet clients’ costs have been increased to billions of dollars for each year due to phishing. Phishers use parodied email, Uniform Resource Locator (URL) locations of phony sites, and phishing programming to take individual data and monetary record subtleties, for example, usernames and passwords. The boycott system is definitely not a sufficient method to remain safe from the cybercriminals. Hence, phishing site pointers must be considered for this reason, with the presence and utilization of machine learning calculations. The current techniques make utilization of all separated attributes in the phishing URL location, prompting high false positive rate.
Cite this Research Publication :
Sountharrajan, S., Nivashini, M., Shandilya, S.K., Suganya, E., Bazila Banu, A. and Karthiga, M., 2020. Dynamic recognition of phishing URLs using deep learning techniques. In Advances in cyber security analytics and decision systems (pp. 27-56). Springer, Cham.