Author: Valiyaveedu, N.; Jamal, S.; Reju, R.; Murali, V.; Nithin K, N. K. M.
Title: Survey and Analysis on AI Based Phishing Detection Techniques Cord-id: 90jihpce Document date: 2021_1_1
ID: 90jihpce
Snippet: From the emergence of networking technologies and the access to websites, there are always threats associated in one way or the other to a user. Cyber Attacks has been a major problem. Even during the current pandemic situation of Covid-19 we have seen an escalation in the number of cyberattacks. There are many kinds of attacks, phishing being one of them. There has been a rise in the number of phishing attacks recently and many prestigious companies like Facebook have been victims of such attac
Document: From the emergence of networking technologies and the access to websites, there are always threats associated in one way or the other to a user. Cyber Attacks has been a major problem. Even during the current pandemic situation of Covid-19 we have seen an escalation in the number of cyberattacks. There are many kinds of attacks, phishing being one of them. There has been a rise in the number of phishing attacks recently and many prestigious companies like Facebook have been victims of such attacks. Thus, it is observable that phishing attacks have been a major issue in the IT sector and it must be taken into account seriously. In this paper we try to efficiently study and analyse the detection of phishing sites that have been haunting people since the emergence of the internet era.Three types of detection techniques have been discussed in this paper: An HTML detection method, URL detection methods and lastly the visual similarity based approach. © 2021 IEEE.
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