Phishing is a technique under Social Engineering attacks which is most widely used to get user sensitive information,such as login credentials and credit and debit card information,*** is carried out by a person masqu...
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Phishing is a technique under Social Engineering attacks which is most widely used to get user sensitive information,such as login credentials and credit and debit card information,*** is carried out by a person masquerading as an authentic *** protect web users from these attacks,various anti-phishing techniques are developed,but they fail to protect the user from these attacks in various *** this paper,we propose a novel technique to identify phishing websites effortlessly on the client side by proposing a novel browser *** this system,we use the rule of extraction framework to extract the properties or features of a website using the URL *** list consists of 30 different properties of a URL,which will later be used by the Random Forest Classification machine learning model to detect the authenticity of the website.A dataset consisting of 11,055 tuples is used to train the *** processes are carried out on the client-side with the help of a redesigned browser *** Researches have come up with machine learning frameworks to detect phishing sites,but they are not in a state to be used by individuals having no technical *** make sure that these tools are accessible to every individual,we have improvised and introduced detection methods into the browser architecture named as‘Embedded Phishing Detection Browser’(EPDB),which is a novel method to preserve the existing user experience while improving the *** newly designed browser architecture introduces a special segment to perform phishing detection operations in *** have prototyped this technique to ensure maximum security,better accuracy of 99.36% in the identification of phishing websites in realtime.
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