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Development of anti-phishing browser based on random forest and rule of extraction framework

Cybersecurity 2018年第1期1卷 879-892页

作者： Mohith Gowda HR Adithya MV Gunesh Prasad S Vinay S B.E in Computer Science and Engineering PES College of Engineering4011Vasuda Krupa3rd CrossShankar NagarMandyaKarnataka 571401India B.E in Computer Science and Engineering PES College of Engineering19321st Main RoadHalahalli ExtNear Vinayaka Auto StandMandyaKarnataka 571401India B.E in Computer Science and Engineering PES College of Engineering20/195th crossShakthi NagarNear Shakthi Nagar ParkMysoreKarnataka 570019India Information Science and Engineering PES College of EngineeringPES Engineering College RdPES College CampusMandyaKarnataka 571401India

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.

关键词： Phishing attack Machine learning Intelligent browser engine rule of extraction algorithm Browser architecture

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